SwePub - sökning: hsv:(ENGINEERING AND TECHNOLOG...

Numrering	Referens	Omslagsbild	Hitta
1.	Abbaspour, S., et al. (författare) Real-Time and Offline Evaluation of Myoelectric Pattern Recognition for the Decoding of Hand Movements 2021 Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 21:16 Tidskriftsartikel (refereegranskat)abstract Pattern recognition algorithms have been widely used to map surface electromyographic signals to target movements as a source for prosthetic control. However, most investigations have been conducted offline by performing the analysis on pre-recorded datasets. While real-time data analysis (i.e., classification when new data becomes available, with limits on latency under 200-300 milliseconds) plays an important role in the control of prosthetics, less knowledge has been gained with respect to real-time performance. Recent literature has underscored the differences between offline classification accuracy, the most common performance metric, and the usability of upper limb prostheses. Therefore, a comparative offline and real-time performance analysis between common algorithms had yet to be performed. In this study, we investigated the offline and real-time performance of nine different classification algorithms, decoding ten individual hand and wrist movements. Surface myoelectric signals were recorded from fifteen able-bodied subjects while performing the ten movements. The offline decoding demonstrated that linear discriminant analysis (LDA) and maximum likelihood estimation (MLE) significantly (p < 0.05) outperformed other classifiers, with an average classification accuracy of above 97%. On the other hand, the real-time investigation revealed that, in addition to the LDA and MLE, multilayer perceptron also outperformed the other algorithms and achieved a classification accuracy and completion rate of above 68% and 69%, respectively.
2.	Bondesson, Johan, 1991, et al. (författare) Definition of Tubular Anatomic Structures from Arbitrary Stereo Lithographic Surface 2017 Ingår i: Initiative Seminar Engineering Health, 8-9 November 2017, Chalmers. Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract An accurate description of anatomies and dynamics of vessels is crucial to understand their characteristics and improve surgical techniques, thus it is the basis, in addition to surgeon experience, on which stent design and operation procedures rely. The process of producing this description is user intensive, and recent improvement in image processing of medical3D imaging allows for a more automated workflow. However, there is a need to bridge the gap from a processed geometry to a robust mathematical computational grid. By sequentially segmenting a tubular anatomic structure, here defined by a stereo lithographic (STL) surface, an initial centerline is formed by connecting centroids of orthogonal cross-sectional contours along the length of the structure. Relying on the initial centerline, a set of non-overlapping 2D cross sectional contours are defined along the centerline, a centerline which is updated after the 2D contours are produced. After a second iteration of producing 2D contours and updating the centerline, a full description of the structure is created. Our method for describing vessel geometry shows good coherence to existing method. The main advantages of our method include the possibility of having arbitrary triangulated STL surface input, automated centerline definition, safety against intersecting cross-sectional contours and automatic clean-up of local kinks and wrinkles.
3.	Lui, Hoi-Shun, et al. (författare) On the matching medium for microwave stroke diagnosis 2019 Ingår i: Biomedical Physics and Engineering Express. - : IOP Publishing. - 2057-1976. ; 5:4 Tidskriftsartikel (refereegranskat)abstract The choice of matching medium can directly affect the amount of power transmitted into and through human bodies, which impacts on the quality of the reconstructed images in microwave-based medical imaging, and thus the diagnosis accuracies. In this paper, the amount of the transmitted and reflected power of multi-layer planar healthy and hemorrhagic stroke brain models under different choices of matching medium are determined. These multi-layer planar brain tissue models are made up of at least 17 tissue layers with realistic dielectric properties. A layer of blood with different thickness is introduced to model the case of hemorrhagic stroke. Our results show that matching medium with low relative permittivity provides better intrinsic contrast between healthy brain and hemorrhagic brain. Analysis on how the reflection coefficient and transmittance vary under different matching medium are included to provide better insights to the findings.
4.	Khodadad, Davood, 1985-, et al. (författare) Optimized breath detection algorithm in electrical impedance tomography 2018 Ingår i: Physiological Measurement. - : IOP Publishing. - 0967-3334 .- 1361-6579. ; 39:9 Tidskriftsartikel (refereegranskat)abstract Objective: This paper defines a method for optimizing the breath delineation algorithms used in electrical impedance tomography (EIT). In lung EIT the identification of the breath phases is central for generating tidal impedance variation images, subsequent data analysis and clinical evaluation. The optimisation of these algorithms is particularly important in neonatal care since the existing breath detectors developed for adults may give insufficient reliability in neonates due to their very irregular breathing pattern.Approach: Our approach is generic in the sense that it relies on the definition of a gold standard and the associated definition of detector sensitivity and specificity, an optimisation criterion and a set of detector parameters to be investigated. The gold standard has been defined by 11 clinicians with previous experience with EIT and the performance of our approach is described and validated using a neonatal EIT dataset acquired within the EU-funded CRADL project.Main results: Three different algorithms are proposed that improve the breath detector performance by adding conditions on (1) maximum tidal breath rate obtained from zero-crossings of the EIT breathing signal, (2) minimum tidal impedance amplitude and (3) minimum tidal breath rate obtained from time-frequency analysis. As a baseline a zero-crossing algorithm has been used with some default parameters based on the Swisstom EIT device.Significance: Based on the gold standard, the most crucial parameters of the proposed algorithms are optimised by using a simple exhaustive search and a weighted metric defined in connection with the receiver operating characterics. This provides a practical way to achieve any desirable trade-off between the sensitivity and the specificity of the detectors.
5.	Y Banaem, Hossein, et al. (författare) Brain tumor modeling : glioma growth and interaction with chemotherapy 2011 Ingår i: International Conference on Graphic and Image Processing (ICGIP 2011). - : SPIE. ; 8285 Konferensbidrag (refereegranskat)abstract In last decade increasingly mathematical models of tumor growths have been studied, particularly on solid tumors which growth mainly caused by cellular proliferation. In this paper we propose a modified model to simulate the growth of gliomas in different stages. Glioma growth is modeled by a reaction-advection-diffusion. We begin with a model of untreated gliomas and continue with models of polyclonal glioma following chemotherapy. From relatively simple assumptions involving homogeneous brain tissue bounded by a few gross anatomical landmarks (ventricles and skull) the models have been expanded to include heterogeneous brain tissue with different motilities of glioma cells in grey and white matter. Tumor growth is characterized by a dangerous change in the control mechanisms, which normally maintain a balance between the rate of proliferation and the rate of apoptosis (controlled cell death). Result shows that this model closes to clinical finding and can simulate brain tumor behavior properly.
6.	Isaksson-Daun, Johan (författare) A Sound Approach Toward a Mobility Aid for Blind and Low-Vision Individuals 2023 Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract Reduced independent mobility of blind and low-vision individuals (BLVIs) cause considerable societal cost, burden on relatives, and reduced quality of life for the individuals, including increased anxiety, depression symptoms, need of assistance, risk of falls, and mortality. Despite the numerous electronic travel aids proposed since at least the 1940’s, along with ever-advancing technology, the mobility issues persist. A substantial reason for this is likely several and severe shortcomings of the field, both in regards to aid design and evaluation.In this work, these shortcomings are addressed with a generic design model called Desire of Use (DoU), which describes the desire of a given user to use an aid for a given activity. It is then applied on mobility of BLVIs (DoU-MoB), to systematically illuminate and structure possibly all related aspects that such an aid needs to aptly deal with, in order for it to become an adequate aid for the objective. These aspects can then both guide user-centered design as well as choice of test methods and measures.One such measure is then demonstrated in the Desire of Use Questionnaire for Mobility of Blind and Low-Vision Individuals (DoUQ-MoB), an aid-agnostic and comprehensive patient-reported outcome measure. The question construction originates from the DoU-MoB to ensure an encompassing focus on mobility of BLVIs, something that has been missing in the field. Since it is aid-agnostic it facilitates aid comparison, which it also actively promotes. To support the reliability of the DoUQ-MoB, it utilizes the best known practices of questionnaire design and has been validated once with eight orientation and mobility professionals, and six BLVIs. Based on this, the questionnaire has also been revised once.To allow for relevant and reproducible methodology, another tool presented herein is a portable virtual reality (VR) system called the Parrot-VR. It uses a hybrid control scheme of absolute rotation by tracking the user’s head in reality, affording intuitive turning; and relative movement where simple button presses on a controller moves the virtual avatar forward and backward, allowing for large-scale traversal while not walking physically. VR provides excellent reproducibility, making various aggregate movement analysis feasible, while it is also inherently safe. Meanwhile, the portability of the system facilitates testing near the participants, substantially increasing the number of potential blind and low-vision recruits for user tests.The thesis also gives a short account on the state of long-term testing in the field; it being short is mainly due to that there is not much to report. It then provides an initial investigation into possible outcome measures for such tests by taking instruments in use by Swedish orientation and mobility professionals as a starting point. Two of these are also piloted in an initial single-session trial with 19 BLVIs, and could plausibly be used for long-term tests after further evaluation.Finally, a discussion is presented regarding the Audomni project — the development of a primary mobility aid for BLVIs. Audomni is a visuo-auditory sensory supplementation device, which aims to take visual information and translate it to sound. A wide field-of-view, 3D-depth camera records the environment, which is then transformed to audio through the sonification algorithms of Audomni, and finally presented in a pair of open-ear headphones that do not block out environmental sounds. The design of Audomni leverages the DoU-MoB to ensure user-centric development and evaluation, in the aim of reaching an aid with such form and function that it grants the users better mobility, while the users still want to use it.Audomni has been evaluated with user tests twice, once in pilot tests with two BLVIs, and once in VR with a heterogenous set of 19 BLVIs, utilizing the Parrot-VR and the DoUQ-MoB. 76 % of responders (13 / 17) answered that it was very or extremely likely that they would want use Audomni along with their current aid. This might be the first result in the field demonstrating a majority of blind and low-vision participants reporting that they actually want to use a new electronic travel aid. This shows promise that eventual long-term tests will demonstrate an increased mobility of blind and low-vision users — the overarching project aim. Such results would ultimately mean that Audomni can become an aid that alleviates societal cost, reduces burden on relatives, and improves users’ quality of life and independence.
7.	Grishenkov, Dmitry, 1983-, et al. (författare) In search of the optimal ultrasound heart perfusion imaging platform 2015 Ingår i: Journal of ultrasound in medicine. - : Wiley. - 0278-4297 .- 1550-9613. ; 34:9, s. 1599-1605 Tidskriftsartikel (refereegranskat)abstract ObjectiveQuantification of the myocardial perfusion by contrast echocardiography (CEC) remains a challenge. Existing imaging phantoms used to evaluate the performance of ultrasound scanners do not comply with perfusion basics in the myocardium, where perfusion and motion are inherently coupled.MethodsTo contribute towards an improvement, we developed a CEC perfusion imaging platform based on isolated rat heart coupled to the ultrasound scanner. Perfusion was assessed using three different types of contrast agent: dextran-based Promiten®, phospholipid-shelled SonoVue®, and polymer-shelled MB-pH5-RT. The myocardial video-intensity was monitored over time from contrast administration to peak and two characteristic constants were calculated using exponential fit (A representing capillary volume and b representing inflow velocity).ResultsAcquired experimental evidence demonstrates that the application of all three types of contrast agent allow ultrasonic estimation of myocardial perfusion in the isolated rat heart. Video-intensity maps show that an increase in contrast concentration increases the late plateau values, A, mimicking increased capillary volume. Estimated values of the flow, proportional to Axb, increase when the pressure of the perfusate column increases from 80 to 110 cm of water. This finding is in agreement with the true values of the coronary flow increase measured by the flowmeter attached to the aortic cannula.ConclusionsThe described CEC perfusion imaging platform holds promise for standardized evaluation and optimization of ultrasound contrast perfusion imaging where real time inflow curves at low acoustic power semi-quantitatively reflect coronary flow.
8.	Kothapalli, Veera Venkata Satya Naray, 1985-, et al. (författare) Unique pumping-out fracturing mechanism of a polymer-shelled contrast agent : An acoustic characterization and optical visualization 2014 Ingår i: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control. - 0885-3010 .- 1525-8955. ; 62:3, s. 451-462 Tidskriftsartikel (refereegranskat)abstract This work describes the fracturing mechanism of air-filled microbubbles (MBs) encapsulated by a cross-linked poly(vinyl alcohol) (PVA) shell. The radial oscillation and fracturing events following the ultrasound exposure were visualized with an ultrahigh-speed camera, and backscattered timedomain signals were acquired with the acoustic setup specific for harmonic detection. No evidence of gas emerging from defects in the shell with the arrival of the first insonation burst was found. In optical recordings, more than one shell defect was noted, and the gas core was drained without any sign of air extrusion when several consecutive bursts of 1 MPa amplitude were applied. In acoustic tests, the backscattered peak-to-peak voltage gradually reached its maximum and exponentially decreased when the PVA-based MB suspension was exposed to approximately 20 consecutive bursts arriving at pulse repetition frequencies of 100 and 500 Hz. Taking into account that the PVA shell is porous and possibly contains large air pockets between the cross-linked PVA chains, the aforementioned acoustic behavior might be attributed to pumping gas from these pockets in combination with gas release from the core through shell defects. We refer to this fracturing mechanism as pumping-out behavior, and this behavior could have potential use for the local delivery of therapeutic gases, such as nitric oxide.
9.	Borrelli, P., et al. (författare) Artificial intelligence-aided CT segmentation for body composition analysis: a validation study 2021 Ingår i: European Radiology Experimental. - : Springer Science and Business Media LLC. - 2509-9280. ; 5:1 Tidskriftsartikel (refereegranskat)abstract BackgroundBody composition is associated with survival outcome in oncological patients, but it is not routinely calculated. Manual segmentation of subcutaneous adipose tissue (SAT) and muscle is time-consuming and therefore limited to a single CT slice. Our goal was to develop an artificial-intelligence (AI)-based method for automated quantification of three-dimensional SAT and muscle volumes from CT images.MethodsEthical approvals from Gothenburg and Lund Universities were obtained. Convolutional neural networks were trained to segment SAT and muscle using manual segmentations on CT images from a training group of 50 patients. The method was applied to a separate test group of 74 cancer patients, who had two CT studies each with a median interval between the studies of 3days. Manual segmentations in a single CT slice were used for comparison. The accuracy was measured as overlap between the automated and manual segmentations.ResultsThe accuracy of the AI method was 0.96 for SAT and 0.94 for muscle. The average differences in volumes were significantly lower than the corresponding differences in areas in a single CT slice: 1.8% versus 5.0% (p <0.001) for SAT and 1.9% versus 3.9% (p < 0.001) for muscle. The 95% confidence intervals for predicted volumes in an individual subject from the corresponding single CT slice areas were in the order of 20%.Conclusions The AI-based tool for quantification of SAT and muscle volumes showed high accuracy and reproducibility and provided a body composition analysis that is more relevant than manual analysis of a single CT slice.
10.	Broman, Mikael, et al. (författare) Recirculation during veno-venous extra-corporeal membrane oxygenation - a simulation study 2015 Ingår i: International Journal of Artificial Organs. - : SAGE Publications. - 0391-3988 .- 1724-6040. ; 38:1, s. 23-30 Tidskriftsartikel (refereegranskat)abstract Purpose: Veno-venous ECMO is indicated in reversible life-threatening respiratory failure without life-threatening circulatory failure. Recirculation of oxygenated blood in the ECMO circuit decreases efficiency of patient oxygen delivery but is difficult to measure. We seek to identify and quantify some of the factors responsible for recirculation in a simulation model and compare with clinical data. Methods: A closed-loop real-time simulation model of the cardiovascular system has been developed. ECMO is simulated with a fixed flow pump 0 to 5 l/min with various cannulation sites -1) right atrium to inferior vena cava, 2) inferior vena cava to right atrium, and 3) superior+ inferior vena cava to right atrium. Simulations are compared to data from a retrospective cohort of 11 consecutive adult veno-venous ECMO patients in our department. Results: Recirculation increases with increasing ECMO-flow, decreases with increasing cardiac output, and is highly dependent on choice of cannulation sites. A more peripheral drainage site decreases recirculation substantially. Conclusions: Simulations suggest that recirculation is a significant clinical problem in veno-venous ECMO in agreement with clinical data. Due to the difficulties in measuring recirculation and interpretation of the venous oxygen saturation in the ECMO drainage blood, flow settings and cannula positioning should rather be optimized with help of arterial oxygenation parameters. Simulation may be useful in quantification and understanding of recirculation in VV-ECMO.
11.	Cervin, Ida, et al. (författare) Improving the creation and reporting of structured findings during digital pathology review 2016 Ingår i: Journal of Pathology Informatics. - : Medknow Publications. - 2229-5089 .- 2153-3539. ; 7:1, s. 32-32 Tidskriftsartikel (refereegranskat)abstract Background: Today, pathology reporting consists of many separate tasks, carried out by multiple people. Common tasks include dictation during case review, transcription, verification of the transcription, report distribution, and report the key findings to follow-up registries. Introduction of digital workstations makes it possible to remove some of these tasks and simplify others. This study describes the work presented at the Nordic Symposium on Digital Pathology 2015, in Linköping, Sweden. Methods: We explored the possibility to have a digital tool that simplifies image review by assisting note-taking, and with minimal extra effort, populates a structured report. Thus, our prototype sees reporting as an activity interleaved with image review rather than a separate final step. We created an interface to collect, sort, and display findings for the most common reporting needs, such as tumor size, grading, and scoring. Results: The interface was designed to reduce the need to retain partial findings in the head or on paper, while at the same time be structured enough to support automatic extraction of key findings for follow-up registry reporting. The final prototype was evaluated with two pathologists, diagnosing complicated partial mastectomy cases. The pathologists experienced that the prototype aided them during the review and that it created a better overall workflow. Conclusions: These results show that it is feasible to simplify the reporting tasks in a way that is not distracting, while at the same time being able to automatically extract the key findings. This simplification is possible due to the realization that the structured format needed for automatic extraction of data can be used to offload the pathologists' working memory during the diagnostic review.
12.	Grönlund, Christer, et al. (författare) Imaging two-dimensional mechanical waves of skeletal muscle contraction 2013 Ingår i: Ultrasound in Medicine and Biology. - : Elsevier BV. - 0301-5629 .- 1879-291X. ; 39:2, s. 360-369 Tidskriftsartikel (refereegranskat)abstract Skeletal muscle contraction is related to rapid mechanical shortening and thickening. Recently, specialized ultrasound systems have been applied to demonstrate and quantify transient tissue velocities and one-dimensional (1-D) propagation of mechanical waves during muscle contraction. Such waves could potentially provide novel information on musculoskeletal characteristics, function and disorders. In this work, we demonstrate two-dimensional (2-D) mechanical wave imaging following the skeletal muscle contraction. B-mode image acquisition during multiple consecutive electrostimulations, speckle-tracking and a time-stamp sorting protocol were used to obtain 1.4 kHz frame rate 2-D tissue velocity imaging of the biceps brachii muscle contraction. The results present novel information on tissue velocity profiles and mechanical wave propagation. In particular, counter-propagating compressional and shear waves in the longitudinal direction were observed in the contracting tissue (speed 2.8-4.4 m/s) and a compressional wave in the transverse direction of the non-contracting muscle tissue (1.2-1.9 m/s). In conclusion, analysing transient 2-D tissue velocity allows simultaneous assessment of both active and passive muscle tissue properties. (E-mail: christer.gronlund@vll.se) (C) 2013 World Federation for Ultrasound in Medicine & Biology.
13.	Mendrik, AM, et al. (författare) MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans 2015 Ingår i: Computational Intelligence and Neuroscience. - : Hindawi Publishing Corporation. - 1687-5265 .- 1687-5273. ; 2015 Tidskriftsartikel (refereegranskat)abstract Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain MRI scans of elderly subjects (65–80 y). Participants apply their algorithms to the provided data, after which their results are evaluated and ranked. Full manual segmentations of GM, WM, and CSF are available for all scans and used as the reference standard. Five datasets are provided for training and fifteen for testing. The evaluated methods are ranked based on their overall performance to segment GM, WM, and CSF and evaluated using three evaluation metrics (Dice, H95, and AVD) and the results are published on the MRBrainS13 website. We present the results of eleven segmentation algorithms that participated in the MRBrainS13 challenge workshop at MICCAI, where the framework was launched, and three commonly used freeware packages: FreeSurfer, FSL, and SPM. The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand.
14.	Nilsson, Daniel, et al. (författare) Patient-specific brain arteries molded as a flexible phantom model using 3D printed water-soluble resin 2022 Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 12 Tidskriftsartikel (refereegranskat)abstract Visualizing medical images from patients as physical 3D models (phantom models) have many roles in the medical field, from education to preclinical preparation and clinical research. However, current phantom models are generally generic, expensive, and time-consuming to fabricate. Thus, there is a need for a cost- and time-efficient pipeline from medical imaging to patient-specific phantom models. In this work, we present a method for creating complex 3D sacrificial molds using an off-the-shelf water-soluble resin and a low-cost desktop 3D printer. This enables us to recreate parts of the cerebral arterial tree as a full-scale phantom model (10×6×410×6×4 cm) in transparent silicone rubber (polydimethylsiloxane, PDMS) from computed tomography angiography images (CTA). We analyzed the model with magnetic resonance imaging (MRI) and compared it with the patient data. The results show good agreement and smooth surfaces for the arteries. We also evaluate our method by looking at its capability to reproduce 1 mm channels and sharp corners. We found that round shapes are well reproduced, whereas sharp features show some divergence. Our method can fabricate a patient-specific phantom model with less than 2 h of total labor time and at a low fabrication cost.
15.	Sabernaeemi, Amir, et al. (författare) Influence of stent-induced vessel deformation on hemodynamic feature of bloodstream inside ICA aneurysms 2023 Ingår i: Biomechanics and Modeling in Mechanobiology. - : Springer Science and Business Media LLC. - 1617-7959 .- 1617-7940. ; 22:4, s. 1193-1207 Tidskriftsartikel (refereegranskat)abstract One of the effective treatment options for intracranial aneurysms is stent-assisted coiling. Though, previous works have demonstrated that stent usage would result in the deformation of the local vasculature. The effect of simple stent on the blood hemodynamics is still uncertain. In this work, hemodynamic features of the blood stream on four different ICA aneurysm with/without interventional are investigated. To estimate the relative impacts of vessel deformation, four distinctive ICA aneurysm is simulated by the one-way FSI technique. Four hemodynamic factors of aneurysm blood velocity, wall pressure and WSS are compared in the peak systolic stage to disclose the impact of defamation by the stent in two conditions. The stent usage would decrease almost all of the mentioned parameters, except for OSI. Stenting reduces neck inflow rate, while the effect of interventional was not consistent among the aneurysms. The deformation of an aneurysm has a strong influence on the hemodynamics of an aneurysm. This outcome is ignored by most of the preceding investigations, which focused on the pre-interventional state for studying the relationship between hemodynamics and stents. Present results show that the application of stent without coiling would improve most hemodynamic factors, especially when the deformation of the aneurysm is high enough.
16.	Tampu, Iulian Emil, et al. (författare) Deep-learning for thyroid microstructure segmentation in 2D OCT images 2021 Ingår i: Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXV. - : SPIE - International Society for Optical Engineering. Konferensbidrag (refereegranskat)abstract Optical coherence tomography (OCT) can provide exquisite details of tissue microstructure without traditional tissue sectioning, with potential diagnostic and intraoperative applications in a variety of clinical areas. In thyroid surgery, OCT could provide information to reduce the risk of damaging normal tissue. Thyroid tissue's follicular structure alters in case of various pathologies including the non-malignant ones which can be imaged using OCT. The success of deep learning for medical image analysis encourages its application on OCT thyroid images for quantitative analysis of tissue microstructure. To investigate the potential of a deep learning approach to segment the follicular structure in OCT images, a 2D U-Net was trained on b-scan OCT images acquired from ex vivo adult human thyroid samples a effected by a range of pathologies. Results on a pool of 104 annotated images showed a mean Dice score of 0.74±0.19 and 0.92±0.09 when segmenting the follicular structure and the surrounding tissue on the test dataset (n=10 images). This study shows that a deep learning approach for tissue microstructure segmentation in OCT images is possible. The achieved performance without requiring manual intervention encourages the application of a deep-learning method for real-time analysis of OCT data.
17.	Yousefi, Hossein, et al. (författare) An optimised linear mechanical model for estimating brain shift caused by meningioma tumours 2013 Ingår i: International Journal of Biomedical Science and Engineering. - : Science Publishing Group. - 2376-7227 .- 2376-7235. ; 1:1, s. 1-9 Tidskriftsartikel (refereegranskat)abstract Estimation of brain deformation plays an important role in computer-aided therapy and image-guided neurosurgery systems. Tumour growth can cause brain deformation and change stress distribution in the brain. Biomechanical models exist that use a finite element method to estimate brain shift caused by tumour growth. Such models can be categorised as linear and non-linear models, both of which assume finite deformation of the brain after tumour growth. Linear models are easy to implement and fast enough to for applications such as IGS where the time is a great of concern. However their accuracy highly dependent on the parameters of the models in this paper, we proposed an optimisation approach to improve a naive linear model to achieve more precise estimation of brain displacements caused by tumour growth. The optimisation process has improved the accuracy of the model by adapting the brain model parameters according to different tomour sizes.We used patient-based tetrahedron finite element mesh with proper material properties for brain tissue and appropriate boundary conditions in the tumour region. Anatomical landmarks were determined by an expert and were divided into two different sets for evaluation and optimisation. Tetrahedral finite element meshes were used and the model parameters were optimised by minimising the mean square distance between the predicted locations of the anatomical landmarks derived from Brain Atlas images and their actual locations on the tumour images. Our results demonstrate great improvement in the accuracy of an optimised linear mechanical model that achieved an accuracy rate of approximately 92%.
18.	Fredén Jansson, Karl-Johan, 1988 (författare) The Balanced Electromagnetic Separation Transducer for Bone Conduction Audiometry and Hearing Rehabilitation 2017 Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract Hearing via air conduction (AC) and bone conduction (BC) are attributed to bethe natural ways of conducting sound to the cochlea. With AC hearing, air pressurevariations are transmitted to the cochlea via the ear canal, whereas with BChearing, sound vibrations are transmitted through the skull bone to the cochlea.Patients with a hearing loss in the cochlea or auditory nerve are commonly rehabilitatedwith conventional AC hearing aids in the ear canal, but also using cochlearimplants. If the pathway for AC sound to reach the cochlea is obstructed, patientscan often benet from bone conduction devices (BCDs). In order to determinethe type and degree of hearing loss, the BC hearing thresholds are measured usinga bone conduction vibrator, and then analyzed together with the AC hearingthresholds for the diagnosis and to suggest an appropriate rehabilitation alternative.The motor unit in conventional BCDs and bone vibrators are known togenerate high amount of distortion at low frequencies where the Balanced ElectromagneticSeparation Transducer (BEST) principle may oer a new era in BChearing rehabilitation and audiometry.This thesis combines two BC hearing related topics, where the rst topic is anevaluation of a new audiometric bone vibrator, Radioear B81, which is assumedto oer more accurate BC hearing threshold measurements. The second topic isrelated to a new type of active transcutaneous BCD, called the Bone ConductionImplant (BCI), which leaves the skin intact by using a wireless solution thatdoes not require a permanent skin penetration. Even though the applications aredierent, both devices use the BEST principle as motor unit in their design.The audiometric bone vibrator Radioear B81 was found to have an improvedperformance at low frequencies where it can produce higher output levels with lessharmonic distortion than the conventional Radioear B71. In a clinical study of therst six patients, the BCI was found as ecient as already commercially availableBCDs, and with the advantage of not needing a skin penetration. In a technicalevaluation of the BCI, it was shown to be a mechanically robust design and totolerate magnetic resonance imaging at 1.5 Tesla.
19.	Khodadad, Davood, 1985-, et al. (författare) The Value of Phase Angle in Electrical Impedance Tomography Breath Detection 2018 Ingår i: 2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama). - : Electromagnetics Academy. - 9784885523168 - 9781538654552 ; , s. 1040-1043 Konferensbidrag (refereegranskat)abstract The objective of this paper is to report our investigation demonstrating that the phase angle information of complex impedance could be a simple indicator of a breath cycle in chest Electrical Impedance Tomography (EIT). The study used clinical neonatal EIT data. The results show that measurement of the phase angle from complex EIT data can be used as a complementary information for improving the conventional breath detection algorithms.
20.	Alipoor, Mohammad, 1983, et al. (författare) weighted least squares estimation of 4th order diffusion tensors 2013 Ingår i: MICCAI 2013 workshop on computational diffusion MRI. Konferensbidrag (övrigt vetenskapligt/konstnärligt)
21.	Azar, Jimmy, et al. (författare) Automated Classification of Glandular Tissue by Statistical Proximity Sampling 2015 Ingår i: International Journal of Biomedical Imaging. - : Hindawi Limited. - 1687-4188 .- 1687-4196. Tidskriftsartikel (refereegranskat)abstract Due to the complexity of biological tissue and variations in staining procedures, features that are based on the explicit extraction of properties from subglandular structures in tissue images may have difficulty generalizing well over an unrestricted set of images and staining variations. We circumvent this problem by an implicit representation that is both robust and highly descriptive, especially when combined with a multiple instance learning approach to image classification. The new feature method is able to describe tissue architecture based on glandular structure. It is based on statistically representing the relative distribution of tissue components around lumen regions, while preserving spatial and quantitative information, as a basis for diagnosing and analyzing different areas within an image. We demonstrate the efficacy of the method in extracting discriminative features for obtaining high classification rates for tubular formation in both healthy and cancerous tissue, which is an important component in Gleason and tubule-based Elston grading. The proposed method may be used for glandular classification, also in other tissue types, in addition to general applicability as a region-based feature descriptor in image analysis where the image represents a bag with a certain label (or grade) and the region-based feature vectors represent instances.
22.	Ge, Chenjie, 1991, et al. (författare) 3D Multi-Scale Convolutional Networks for Glioma Grading Using MR Images 2018 Ingår i: Proceedings - International Conference on Image Processing, ICIP. - 1522-4880. - 9781479970612 ; , s. 141-145 Konferensbidrag (refereegranskat)abstract This paper addresses issues of grading brain tumor, glioma, from Magnetic Resonance Images (MRIs). Although feature pyramid is shown to be useful to extract multi-scale features for object recognition, it is rarely explored in MRI images for glioma classification/grading. For glioma grading, existing deep learning methods often use convolutional neural networks (CNNs) to extract single-scale features without considering that the scales of brain tumor features vary depending on structure/shape, size, tissue smoothness, and locations. In this paper, we propose to incorporate the multi-scale feature learning into a deep convolutional network architecture, which extracts multi-scale semantic as well as fine features for glioma tumor grading. The main contributions of the paper are: (a) propose a novel 3D multi-scale convolutional network architecture for the dedicated task of glioma grading; (b) propose a novel feature fusion scheme that further refines multi-scale features generated from multi-scale convolutional layers; (c) propose a saliency-aware strategy to enhance tumor regions of MRIs. Experiments were conducted on an open dataset for classifying high/low grade gliomas. Performance on the test set using the proposed scheme has shown good results (with accuracy of 89.47%).
23.	Ge, Chenjie, 1991, et al. (författare) Multiscale Deep Convolutional Networks for Characterization and Detection of Alzheimer's Disease using MR Images 2019 Ingår i: Proceedings - International Conference on Image Processing, ICIP. - 1522-4880. ; 2019-September, s. 789-793 Konferensbidrag (refereegranskat)abstract This paper addresses the issues of Alzheimer's disease (AD) characterization and detection from Magnetic Resonance Images (MRIs). Many existing AD detection methods use single-scale feature learning from brain scans. In this paper, we propose a multiscale deep learning architecture for learning AD features. The main contributions of the paper include: (a) propose a novel 3D multiscale CNN architecture for the dedicated task of AD detection; (b) propose a feature fusion and enhancement strategy for multiscale features; (c) empirical study on the impact of several settings, including two dataset partitioning approaches, and the use of multiscale and feature enhancement. Experiments were conducted on an open ADNI dataset (1198 brain scans from 337 subjects), test results have shown the effectiveness of the proposed method with test accuracy of 93.53%, 87.24% (best, average) on subject separated dataset, and 99.44%, 98.80% (best, average) on random brain scan-partitioned dataset. Comparison with eight existing methods has provided further support to the proposed method.
24.	Grönlund, Christer, 1975-, et al. (författare) Significant beat-to-beat variability of E/e’ irrespective of respiration 2013 Ingår i: International cardiovascular forum. - : Barcaray Publishing. - 2409-3424 .- 2410-2636. ; 1:2, s. 88-89 Tidskriftsartikel (refereegranskat)abstract The E/e’ ratio is commonly used in Doppler echocardiographic examinations to estimate the pulmonary capillary wedge pressure. The rationale of using this ratio is to combine left ventricular (LV) filling (E) and relaxation (e’) velocities to indirectly assess left atrial pressure. However, the accuracy of this index has recently been questioned, particularly in patients with controlled heart failure. Likewise, the potential beat-to-beat variability of such measurements remains undetermined. The cardiovascular system is subject to several oscillations with the potential of influencing LV function and its intra-cavitary pressures, hence measurements of its filling and relaxation velocities. The aim of this pilot study was to assess the beat-to-beat variability of the E/e’ ratio in one minute long examination in healthy subjects, and patients with various severity of amyloid heart disease. The results show that despite critical application of the standard echocardiographic recording recommendations, E/e’ beat-to-beat variability was 36 % (22 to 50%) in healthy subjects and 17 % (11-26%) in patients, and where the most severe amyloid heart disease had the least variability. Thus, clinical use of a single or few cardiac beats might not necessarily reflect an accurate ratio between the two velocities, and hence casts doubt over their diagnostic value.
25.	Hagberg, Eva, et al. (författare) Semi-supervised learning with natural language processing for right ventricle classification in echocardiography—a scalable approach 2022 Ingår i: Computers in Biology and Medicine. - : Elsevier BV. - 0010-4825 .- 1879-0534. ; 143 Tidskriftsartikel (refereegranskat)abstract We created a deep learning model, trained on text classified by natural language processing (NLP), to assess right ventricular (RV) size and function from echocardiographic images. We included 12,684 examinations with corresponding written reports for text classification. After manual annotation of 1489 reports, we trained an NLP model to classify the remaining 10,651 reports. A view classifier was developed to select the 4-chamber or RV-focused view from an echocardiographic examination (n = 539). The final models were two image classification models trained on the predicted labels from the combined manual annotation and NLP models and the corresponding echocardiographic view to assess RV function (training set n = 11,008) and size (training set n = 9951. The text classifier identified impaired RV function with 99% sensitivity and 98% specificity and RV enlargement with 98% sensitivity and 98% specificity. The view classification model identified the 4-chamber view with 92% accuracy and the RV-focused view with 73% accuracy. The image classification models identified impaired RV function with 93% sensitivity and 72% specificity and an enlarged RV with 80% sensitivity and 85% specificity; agreement with the written reports was substantial (both κ = 0.65). Our findings show that models for automatic image assessment can be trained to classify RV size and function by using model-annotated data from written echocardiography reports. This pipeline for auto-annotation of the echocardiographic images, using a NLP model with medical reports as input, can be used to train an image-assessment model without manual annotation of images and enables fast and inexpensive expansion of the training dataset when needed. © 2022
26.	Hedlund, Joel, 1978-, et al. (författare) Key insights in the AIDA community policy on sharing of clinical imaging data for research in Sweden 2020 Ingår i: Scientific Data. - : Springer Nature. - 2052-4463. ; 7 Tidskriftsartikel (refereegranskat)abstract Development of world-class artificial intelligence (AI) for medical imaging requires access to massive amounts of training data from clinical sources, but effective data sharing is often hindered by uncertainty regarding data protection. We describe an initiative to reduce this uncertainty through a policy describing a national community consensus on sound data sharing practices.
27.	Kober, Cornelia, et al. (författare) Computer assisted assessment of progressing osteoradionecrosis of the jaw for clinical diagnosis and treatment 2016 Ingår i: Current Directions in Biomedical Engineering. - : Walter de Gruyter GmbH. - 2364-5504. ; 2:1, s. 507-510 Tidskriftsartikel (refereegranskat)abstract Osteoradionecrosis (ORN) is a serious side effect of oncologic radiation therapy. Often, surgical removal of the affected skeletal tissue is indicated. In craniomaxillofacial surgery, partial or total resection of the upper or lower jaw implies a severe impairment of the patient‘s quality of life. Up to now, clear display of ORN is still a challenge. This part of the project is dedicated to medical visualization of progressing ORN for clinical diagnosis. Currently, clinical diagnosis of ORN is mostly based on computer tomography (CT). With regard to its high advantages as e.g. reduced radiation dose, we additionally evaluate cone beam computer tomography (CBCT). After registration on a suitable reference and refined image processing and segmentation, all patient’s CT-/CBCT-data are subjected to various rendering techniques configured for the respective purpose, namely visualization of destructive and/or sclerotic skeletal alterations, consideration of cortical or trabecular bone, and analysis based on CT or CBCT. Recent achievements within the project were demonstrated with special focus on evaluation of both, CT and CBCT as well as on close cooperation with the clinical setting.
28.	Lidayová, Kristína, et al. (författare) Fast vascular skeleton extraction algorithm 2016 Ingår i: Pattern Recognition Letters. - : Elsevier. - 0167-8655 .- 1872-7344. ; 76, s. 67-75 Tidskriftsartikel (refereegranskat)abstract Vascular diseases are a common cause of death, particularly in developed countries. Computerized image analysis tools play a potentially important role in diagnosing and quantifying vascular pathologies. Given the size and complexity of modern angiographic data acquisition, fast, automatic and accurate vascular segmentation is a challenging task.In this paper we introduce a fully automatic high-speed vascular skeleton extraction algorithm that is intended as a first step in a complete vascular tree segmentation program. The method takes a 3D unprocessed Computed Tomography Angiography (CTA) scan as input and produces a graph in which the nodes are centrally located artery voxels and the edges represent connections between them. The algorithm works in two passes where the first pass is designed to extract the skeleton of large arteries and the second pass focuses on smaller vascular structures. Each pass consists of three main steps. The first step sets proper parameters automatically using Gaussian curve fitting. In the second step different filters are applied to detect voxels - nodes - that are part of arteries. In the last step the nodes are connected in order to obtain a continuous centerline tree for the entire vasculature. Structures found, that do not belong to the arteries, are removed in a final anatomy-based analysis. The proposed method is computationally efficient with an average execution time of 29s and has been tested on a set of CTA scans of the lower limbs achieving an average overlap rate of 97% and an average detection rate of 71%.
29.	Marlevi, David (författare) Non-invasive imaging for improved cardiovascular diagnostics : Shear wave elastography, relative pressure estimation, and tomographic reconstruction 2019 Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract Throughout the last century, medical imaging has come to revolutionise the way we diagnose disease, and is today an indispensable part of virtually any clinical practice. In cardiovascular care imaging is extensively utilised, and the development of novel techniques promises refined diagnostic abilities: ultrasound elastography allows for constitutive tissue assessment, 4D flow magnetic resonance imaging (MRI) enables full-field flow mapping, and micro-Computed Tomography (CT) permits high-resolution imaging at pre-clinical level. However, following the complex nature of cardiovascular disease, refined methods are still very much needed to accurately utilise these techniques and to effectively isolate disease developments.The aim of this thesis has been to develop such methods for refined cardiovascular image diagnostics. In total eight studies conducted over three separate focus areas have been included: four on vascular shear wave elastography (SWE), three on non-invasive cardiovascular relative pressure estimations, and one on tomographic reconstruction for pre-clinical imaging.In Study I-IV, the accuracy and feasibility of vascular SWE was evaluated, with particular focus on refined carotid plaque characterisation. With confined arterial or plaque tissue restricting acoustic wave propagation, analysis of group and phase velocity was performed with SWE output validated against reference mechanical testing and imaging. The results indicate that geometrical confinement has a significant impact on SWE accuracy, however that a combined group and phase velocity approach can be utilised to identify vulnerable carotid plaque lesions in-vivo.In Study V-VII, a non-invasive method for the interrogation of relative pressure from imaged cardiovascular flow was developed. Using the concept of virtual work-energy, the method was applied to accurately assess relative pressures throughout complex, turbulence-inducing, branching vasculatures. The method was also applied on a dilated cardiomyopathy cohort, indicating arterial hemodynamic changes in cardiac disease.Lastly, in Study VIII a method for multigrid image reconstruction of tomographic data was developed, utilising domain splitting and operator masking to accurately reconstruct high-resolution regions-of-interests at a fraction of the computational cost of conventional full-resolution methods.Together, the eight studies have incorporated a range of different imaging modalities, developed methods for both constitutive and hemodynamic cardiovascular assessment, and utilised refined pre-clinical imaging, all with the same purpose: to refine current state cardiovascular imaging and to improve our ability to non-invasively assess cardiovascular disease. With promising results reached, the studies lay the foundation for continued clinical investigations, advancing the presented methods and maturing their usage for an improved future cardiovascular care.
30.	Molin, Jesper, 1987, et al. (författare) Feature-enhancing zoom to facilitate Ki-67 hot spot detection 2014 Ingår i: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. - : SPIE. - 1605-7422. - 9780819498342 ; 9041 Konferensbidrag (refereegranskat)abstract Image processing algorithms in pathology commonly include automated decision points such as classifications. While this enables efficient automation, there is also a risk that errors are induced. A different paradigm is to use image processing for enhancements without introducing explicit classifications. Such enhancements can help pathologists to increase efficiency without sacrificing accuracy. In our work, this paradigm has been applied to Ki-67 hot spot detection. Ki-67 scoring is a routine analysis to quantify the proliferation rate of tumor cells. Cell counting in the hot spot, the region of highest concentration of positive tumor cells, is a method increasingly used in clinical routine. An obstacle for this method is that while hot spot selection is a task suitable for low magnification, high magnification is needed to discern positive nuclei, thus the pathologist must perform many zooming operations. We propose to address this issue by an image processing method that increases the visibility of the positive nuclei at low magnification levels. This tool displays the modified version at low magnification, while gradually blending into the original image at high magnification. The tool was evaluated in a feasibility study with four pathologists targeting routine clinical use. In a task to compare hot spot concentrations, the average accuracy was 75±4.1% using the tool and 69±4.6% without it (n=4). Feedback on the system, gathered from an observer study, indicate that the pathologists found the tool useful and fitting in their existing diagnostic process. The pathologists judged the tool to be feasible for implementation in clinical routine.
31.	Moshavegh, Ramin, et al. (författare) Automated segmentation of free-lying cell nuclei in Pap smears for malignancy-associated change analysis 2012 Ingår i: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781424441198 ; , s. 5372-5375 Konferensbidrag (refereegranskat)abstract This paper presents an automated algorithm for robustly detecting and segmenting free-lying cell nuclei in bright-field microscope images of Pap smears. This is an essential initial step in the development of an automated screening system for cervical cancer based on malignancy associated change (MAC) analysis. The proposed segmentation algorithm makes use of gray-scale annular closings to identify free-lying nuclei-like objects together with marker-based watershed segmentation to accurately delineate the nuclear boundaries. The algorithm also employs artifact rejection based on size, shape, and granularity to ensure only the nuclei of intermediate squamous epithelial cells are retained. An evaluation of the performance of the algorithm relative to expert manual segmentation of 33 fields-of-view from 11 Pap smear slides is also presented. The results show that the sensitivity and specificity of nucleus detection is 94.71% and 85.30% respectively, and that the accuracy of segmentation, measured using the Dice coefficient, of the detected nuclei is 97.30±1.3%.
32.	Norlén, Alexander, 1988, et al. (författare) Automatic pericardium segmentation and quantification of epicardial fat from computed tomography angiography 2016 Ingår i: Journal of Mecial Imaging. - 2329-4302 .- 2329-4310. ; 3:3 Tidskriftsartikel (refereegranskat)abstract Recent findings indicate a strong correlation between the risk of future heart disease and the volume ofadipose tissue inside of the pericardium. So far, large-scale studies have been hindered by the fact that manual delin-eation of the pericardium is extremely time-consuming and that existing methods for automatic delineation strugglewith accuracy. In this paper, an efficient and fully automatic approach to pericardium segmentation and epicardial fatvolume estimation is presented, based on a variant of multi-atlas segmentation for spatial initialization and a randomforest classifier for accurate pericardium detection. Experimental validation on a set of 30 manually delineated Com-puter Tomography Angiography (CTA) volumes shows a significant improvement on state-of-the-art in terms of EFVestimation (mean absolute epicardial fat volume difference: 3.8 ml (4.7%), Pearson correlation: 0.99) with run-timessuitable for large-scale studies (52 s). Further, the results compare favorably to inter-observer variability measured on10 volumes.
33.	Ostling, Janina, et al. (författare) Novel detector for portal imaging in radiation therapy 2000 Ingår i: Medical Imaging 2000. ; , s. 84-95 Konferensbidrag (refereegranskat)
34.	Persson, Mikael, 1959, et al. (författare) Microwave based diagnostics and treatment in practice 2013 Ingår i: 2013 IEEE MTT-S International Microwave Workshop Series on RF and Wireless Technologies for Biomedical and Healthcare Applications, IMWS-BIO 2013 - Proceedings. Konferensbidrag (refereegranskat)abstract Globally, around 15 million people each year suffer a stroke. Only a small fraction of stroke patients who could benefit from thrombolytic treatment reach diagnosis and treatment in time. To increase this low figure we have developed microwave technology aiming to differentiate hemorrhagic from ischemic stroke patients. The standard method for breast cancer diagnosis today is X-ray mammography. Despite its recognized ability to detect tumors it suffers from some limitations. Neither the false positive nor the false negative detection rates are negligible. An interesting alternative being researched extensively today is microwave tomography. In our current strive to develop a clinical prototype we have found that the most suitable design consists of an antenna array placed in a full 3D pattern. During the last decade clinical studies have demonstrated the ability of microwave hyperthermia to dramatically enhance cancer patient survival. The fundamental challenge is to adequately heat deep-seated tumors while preventing surrounding healthy tissue from undesired heating and damage. We are specifically addressing the challenge to deliver power levels with spatial control, patient treatment planning, and noninvasive temperature measurements. © 2013 IEEE.
35.	Qaiser, Mahmood, 1981 (författare) Automated Patient-Specific Multi-tissue Segmentation of MR Images of the Head 2013 Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract The automated segmentation of magnetic resonance (MR) images of the human head is an active area of research in the field of neuroimaging. The resulting segmentation yields a patient-specific labeling of individual tissues and makes possible quantitative characterization of these tissues (e.g. in the study of Alzheimers disease and multiple sclerosis). The segmentation is also useful for assigning individual tissues conductivity or biomechanical properties for patient-specific electromagnetic and biomechanical simulations respectively. The former are of importance in applications such as EEG (electroencephalography) source localization in epilepsy patients and hyperthermia treatment planning for head and neck tumors. The latter are of interest in applications such as patient-specific motion correction and in surgical simulation.Automated and accurate segmentation of MR images is a challenging task in the field of neuroimaging because of noise, spatial intensity inhomogeneities, difficulty of MR intensity normalization and partial volume effects (a single voxel represents more than one tissue type). Consequently most of the techniques proposed to date require manual correction or intervention to achieve an accurate segmentation of the brain or whole-head. As a result they are time consuming,laborious and subjective. This thesis presents two automatic and unsupervised segmentation methods, for multi-tissue segmentation of the brain and whole-head respectively from multi-modal MR images, that are more accurate than the state-of-the-art algorithms. The brain segmentation method is based on the mean shift algorithm with a Bayesian-based adaptive bandwidth estimator. The method is called BAMS (Bayesian adaptive mean shift) and can be used to segment the brain into multiple tissue types; e.g. white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The accuracy of BAMS was evaluated relative to that of several competing methods using both synthetic and real MRI data. The results show that it is robust to both noise and spatial intensity in- homogeneities compared to competing methods. The whole-head segmentation method is based on a hierarchical segmentation approach (HSA) incorporating the BAMS method. The segmentation performance of HSA-BAMS was evaluated relative to a reference method BET-FAST (based on the BET and FAST tools in the well-known FMRIB Software Library) and three other instantiations of the HSA, using synthetic MRI data with varying noise levels, and real MRI data. The segmentation results show the efficacy and accuracy of proposed method and that it consistently outperforms the BET-FAST reference method. HSA-BAMS was also evaluated indirectly in terms of its impact on the accuracy of EEG source localization using electromagnetic simulations based on a tissue conductivity labeling derived from the segmentation. The results demonstrate that HSA-BAMS outperforms the competing methods, and suggest that it has potential as a surrogate for manual segmentation for EEG source localization.
36.	Shakya, Snehlata, et al. (författare) Multi-fiber estimation and tractography for diffusion mri using mixture of non-central wishart distributions 2017 Ingår i: 2017 Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2017. - : Eurographics Association. - 9783038680369 ; , s. 119-123 Konferensbidrag (refereegranskat)abstract Multi-compartmental models are popular to resolve intra-voxel fiber heterogeneity. One such model is the mixture of central Wishart distributions. In this paper, we use our recently proposed model to estimate the orientations of crossing fibers within a voxel based on mixture of non-central Wishart distributions. We present a thorough comparison of the results from other fiber reconstruction methods with this model. The comparative study includes experiments on a range of separation angles between crossing fibers, with different noise levels, and on real human brain diffusion MRI data. Furthermore, we present multi-fiber visualization results using tractography. Results on synthetic and real data as well as tractography visualization highlight the superior performance of the model specifically for small and middle ranges of separation angles among crossing fibers.
37.	Spyretos, Christoforos, 1996-, et al. (författare) Classification of Brain Tumour Tissue in Histopathology Images Using Deep Learning 2023 Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract Deep learning models have achieved prominent performance in digital pathology, with the potential to provide healthcare professionals with accurate decision-making assistance in their workflow. In this study, ViT and CNN models were implemented and compared for patch-level classification of four major glioblastoma tissue structures in histology images.A subset of the IvyGAP dataset (41 subjects, 123 images) was used, stain-normalised and patches of size 256x256 pixels were extracted. A per-subject split approach was applied to obtain training, validation and testing sets. Three models were implemented, a ViT and a CNN trained from scratch, and a ViT pre-trained on a different brain tumour histology dataset. The models' performance was assessed using a range of metrics, including accuracy and Matthew's correlation coefficient (MCC). In addition, calibration experiments were conducted and evaluated to align the models with the ground truth, utilising the temperature scaling technique. The models' uncertainty was estimated using the Monte Carlo dropout method. Lastly, the models were compared using the Wilcoxon signed-rank statistical significance test with Bonferroni correction.Among the models, the scratch-trained ViT obtained the highest test accuracy of 67% and an MCC of 0.45. The scratch-trained CNN reached a test accuracy of 49% and an MCC of 0.15, and the pre-trained ViT only achieved a test accuracy of 28% and an MCC of 0.034. Comparing the reliability graphs and metrics before and after applying temperature scaling, the subsequent experiments proceeded with the uncalibrated ViTs and the calibrated CNN. The calibrated CNN demonstrated moderate to high uncertainty across classes, and the ViTs had an overall high uncertainty. Statistically, there was no difference among the models at a significance level of 0.017. In conclusion, the scratch-trained ViT model considerably outperformed the scratch-trained CNN and the pre-trained ViT in classification. However, there was no statistically significant difference among the models.
38.	Tampu, Iulian Emil, et al. (författare) Diseased thyroid tissue classification in OCT images using deep learning: towards surgical decision support 2023 Ingår i: Journal of Biophotonics. - : Wiley. - 1864-063X .- 1864-0648. ; 16:2 Tidskriftsartikel (refereegranskat)abstract Intraoperative guidance tools for thyroid surgery based on optical coherence tomography (OCT) could aid distinguish between normal and diseased tissue. However, OCT images are difficult to interpret, thus, real-time automatic analysis could support the clinical decision-making. In this study, several deep learning models were investigated for thyroid disease classification on 2D and 3D OCT data obtained from ex vivo specimens of 22 patients undergoing surgery and diagnosed with several thyroid pathologies. Additionally, two open-access datasets were used to evaluate the custom models. On the thyroid dataset, the best performance was achieved by the 3D vision transformer model with a Matthews correlation coefficient (MCC) of 0.79 (accuracy = 0.90) for the normal-versus-abnormal classification. On the open-access datasets, the custom models achieved the best performance (MCC > 0.88, accuracy > 0.96). Results obtained for the normal-versus-abnormal classification suggest OCT, complemented with deep learning-based analysis, as a tool for real-time automatic diseased tissue identification in thyroid surgery.
39.	Tampu, Iulian Emil, et al. (författare) Pediatric brain tumor classification using MR-images with age fusion 2024 Konferensbidrag (övrigt vetenskapligt/konstnärligt)
40.	Wang, Chunliang, 1980-, et al. (författare) CT scan range estimation using multiple body parts detection : let PACS learn the CT image content 2016 Ingår i: International Journal of Computer Assisted Radiology and Surgery. - : Springer. - 1861-6410 .- 1861-6429. ; 11:2, s. 317-325 Tidskriftsartikel (refereegranskat)abstract Purpose: The aim of this study was to develop an efficient CT scan range estimation method that is based on the analysis of image data itself instead of metadata analysis. This makes it possible to quantitatively compare the scan range of two studies. Methods: In our study, 3D stacks are first projected to 2D coronal images via a ray casting-like process. Trained 2D body part classifiers are then used to recognize different body parts in the projected image. The detected candidate regions go into a structure grouping process to eliminate false-positive detections. Finally, the scale and position of the patient relative to the projected figure are estimated based on the detected body parts via a structural voting. The start and end lines of the CT scan are projected to a standard human figure. The position readout is normalized so that the bottom of the feet represents 0.0, and the top of the head is 1.0. Results: Classifiers for 18 body parts were trained using 184 CT scans. The final application was tested on 136 randomly selected heterogeneous CT scans. Ground truth was generated by asking two human observers to mark the start and end positions of each scan on the standard human figure. When compared with the human observers, the mean absolute error of the proposed method is 1.2 % (max: 3.5 %) and 1.6 % (max: 5.4 %) for the start and end positions, respectively. Conclusion: We proposed a scan range estimation method using multiple body parts detection and relative structure position analysis. In our preliminary tests, the proposed method delivered promising results.
41.	Wang, Chunliang, 1980-, et al. (författare) Fast level-set based image segmentation using coherent propagation 2014 Ingår i: Medical physics (Lancaster). - : John Wiley and Sons Ltd. - 0094-2405. ; 41:7 Tidskriftsartikel (refereegranskat)abstract Purpose: The level-set method is known to require long computation time for 3D image segmentation, which limits its usage in clinical workflow. The goal of this study was to develop a fast level-set algorithm based on the coherent propagation method and explore its character using clinical datasets. Methods: The coherent propagation algorithm allows level set functions to converge faster by forcing the contour to move monotonically according to a predicted developing trend. Repeated temporary backwards propagation, caused by noise or numerical errors, is then avoided. It also makes it possible to detect local convergence, so that the parts of the boundary that have reached their final position can be excluded in subsequent iterations, thus reducing computation time. To compensate for the overshoot error, forward and backward coherent propagation is repeated periodically. This can result in fluctuations of great magnitude in parts of the contour. In this paper, a new gradual convergence scheme using a damping factor is proposed to address this problem. The new algorithm is also generalized to non-narrow band cases. Finally, the coherent propagation approach is combined with a new distance-regularized level set, which eliminates the needs of reinitialization of the distance. Results: Compared with the sparse field method implemented in the widely available ITKSnap software, the proposed algorithm is about 10 times faster when used for brain segmentation and about 100 times faster for aorta segmentation. Using a multiresolution approach, the new method achieved 50 times speed-up in liver segmentation. The Dice coefficient between the proposed method and the sparse field method is above 99% in most cases. Conclusions: A generalized coherent propagation algorithm for level set evolution yielded substantial improvement in processing time with both synthetic datasets and medical images.
42.	Zanca, Federica, et al. (författare) Diagnostic accuracy of digital mammography versus tomosynthesis : effect of radiologists' experience 2012 Ingår i: Medical Imaging 2012. - International Society for Optics and Photonics : SPIE. - 9780819489678 ; , s. 83180-83180 Konferensbidrag (refereegranskat)abstract Purpose: To investigate whether readers' experience affects performance in a study comparing 2D digital mammography (2D) with 2-view (CC and MLO) or 1-view (MLO) tomosynthesis. Materials and Methods: One-hundred-thirty 2D cases were collected from screening assessment and referral clinics; 64 of the cases had verified abnormalities and the remaining were confirmed normal. Two-view tomosynthesis images were obtained from the same patients. Ten accredited readers (5 with ≥ 10 years experience in mammography and 5 with < 10 years) classified the cases in terms of malignancy (rate 0-5), and recall (yes/no), for both modalities. A second experiment was performed with the same cases, with 10 other readers (again 5 experienced / 5 less experienced), but using 2D and 1-view tomosynthesis as the two modalities. The multi-reader-multi-case ROC method was applied and the significance of diagnostic accuracy difference of 2D vs tomosynthesis was calculated, as a function of experience and for each experiment. Recall rate (RR) on malignant and benign cases was also calculated, along with reading time. Results: No significant difference was reached between 2D and 2-view tomosynthesis for experienced readers (pvalue= 0.25); for less experienced readers the p-value was significant (0.03). No significant difference was found between 2D and 1-view tomosynthesis, independent of readers' experience. RR for benign cases decreased for tomosynthesis (for booth 1- and 2-view), independent of experience. Average reading time per case was 79 s (range 65- 91 s) and 134 s (range 119-158 s) for experienced readers; 56 s (range 46-67 s) and 115s (range 97-142 s) for nonexperienced, for 2D and 2-view tomosynthesis respectively. Reading time was 74 s (range 43-98 s) and 99 s (range 73- 117 s) for experienced readers; 74 s (range 62-85 s) and 94 s (range 82-137 s) for non-experienced, for 2D and 1-view tomosynthesis respectively. Conclusions: For experienced readers, there is no evidence of improved diagnostic accuracy when using 2-view or 1- view tomosynthesis, while less experienced readers perform better with 2-view tomosynthesis than 2D images. Tomosynthesis reduces the number of recall of benign cases, without hindering cancer detection.
43.	Klintström, Benjamin, et al. (författare) Photon-counting detector CT and energy-integrating detector CT for trabecular bone microstructure analysis of cubic specimens from human radius 2022 Ingår i: European radiology experimental. - : Springer Nature. - 2509-9280. ; 6:1 Tidskriftsartikel (refereegranskat)abstract Background As bone microstructure is known to impact bone strength, the aim of this in vitro study was to evaluate if the emerging photon-counting detector computed tomography (PCD-CT) technique may be used for measurements of trabecular bone structures like thickness, separation, nodes, spacing and bone volume fraction. Methods Fourteen cubic sections of human radius were scanned with two multislice CT devices, one PCD-CT and one energy-integrating detector CT (EID-CT), using micro-CT as a reference standard. The protocols for PCD-CT and EID-CT were those recommended for inner- and middle-ear structures, although at higher mAs values: PCD-CT at 450 mAs and EID-CT at 600 (dose equivalent to PCD-CT) and 1000 mAs. Average measurements of the five bone parameters as well as dispersion measurements of thickness, separation and spacing were calculated using a three-dimensional automated region growing (ARG) algorithm. Spearman correlations with micro-CT were computed. Results Correlations with micro-CT, for PCD-CT and EID-CT, ranged from 0.64 to 0.98 for all parameters except for dispersion of thickness, which did not show a significant correlation (p = 0.078 to 0.892). PCD-CT had seven of the eight parameters with correlations rho > 0.7 and three rho > 0.9. The dose-equivalent EID-CT instead had four parameters with correlations rho > 0.7 and only one rho > 0.9. Conclusions In this in vitro study of radius specimens, strong correlations were found between trabecular bone structure parameters computed from PCD-CT data when compared to micro-CT. This suggests that PCD-CT might be useful for analysing bone microstructure in the peripheral human skeleton.
44.	Mürer, Fredrik K., et al. (författare) Quantifying the hydroxyapatite orientation near the ossification front in a piglet femoral condyle using X-ray diffraction tensor tomography 2021 Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 11:1 Tidskriftsartikel (refereegranskat)abstract While a detailed knowledge of the hierarchical structure and morphology of the extracellular matrix is considered crucial for understanding the physiological and mechanical properties of bone and cartilage, the orientation of collagen fibres and carbonated hydroxyapatite (HA) crystallites remains a debated topic. Conventional microscopy techniques for orientational imaging require destructive sample sectioning, which both precludes further studies of the intact sample and potentially changes the microstructure. In this work, we use X-ray diffraction tensor tomography to image non-destructively in 3D the HA orientation in a medial femoral condyle of a piglet. By exploiting the anisotropic HA diffraction signal, 3D maps showing systematic local variations of the HA crystallite orientation in the growing subchondral bone and in the adjacent mineralized growth cartilage are obtained. Orientation maps of HA crystallites over a large field of view (~ 3 × 3 × 3 mm3) close to the ossification (bone-growth) front are compared with high-resolution X-ray propagation phase-contrast computed tomography images. The HA crystallites are found to predominantly orient with their crystallite c-axis directed towards the ossification front. Distinct patterns of HA preferred orientation are found in the vicinity of cartilage canals protruding from the subchondral bone. The demonstrated ability of retrieving 3D orientation maps of bone-cartilage structures is expected to give a better understanding of the physiological properties of bones, including their propensity for bone-cartilage diseases.
45.	Wu, Dan, 1990-, et al. (författare) Young’s modulus of trabecular bone at the tissue level : A review 2018 Ingår i: Acta Biomaterialia. - : Elsevier BV. - 1742-7061 .- 1878-7568. ; 78, s. 1-12 Forskningsöversikt (refereegranskat)abstract The tissue-level Young’s modulus of trabecular bone is important for detailed mechanical analysis of bone and bone-implant mechanical interactions. However, the heterogeneity and small size of the trabecular struts complicate an accurate determination. Methods such as micro-mechanical testing of single trabeculae, ultrasonic testing, and nanoindentation have been used to estimate the trabecular Young’s modulus. This review summarizes and classifies the trabecular Young’s moduli reported in the literature. Information on species, anatomic site, and test condition of the samples has also been gathered. Advantages and disadvantages of the different methods together with recent developments are discussed, followed by some suggestions for potential improvement, for future work. In summary, this review provides a thorough introduction to the approaches used for determining trabecular Young’s modulus, highlights important considerations when applying these methods and summarizes the reported Young’s modulus for follow-up studies on trabecular properties.
46.	Haj-Hosseini, Neda, 1980-, et al. (författare) Early Detection of Oral Potentially Malignant Disorders: A Review on Prospective Screening Methods with Regard to Global Challenges 2024 Ingår i: Journal of Maxillofacial & Oral Surgery. - New Delhi, India : Springer Science and Business Media LLC. - 0972-8279 .- 0974-942X. ; 23:1, s. 23-32 Tidskriftsartikel (refereegranskat)abstract Oral cancer is a cancer type that is widely prevalent in low-and middle-income countries with a high mortality rate, and poor quality of life for patients after treatment. Early treatment of cancer increases patient survival, improves quality of life and results in less morbidity and a better prognosis. To reach this goal, early detection of malignancies using technologies that can be used in remote and low resource areas is desirable. Such technologies should be affordable, accurate, and easy to use and interpret. This review surveys different technologies that have the potentials of implementation in primary health and general dental practice, considering global perspectives and with a focus on the population in India, where oral cancer is highly prevalent. The technologies reviewed include both sample-based methods, such as saliva and blood analysis and brush biopsy, and more direct screening of the oral cavity including fluorescence, Raman techniques, and optical coherence tomography. Digitalisation, followed by automated artificial intelligence based analysis, are key elements in facilitating wide access to these technologies, to non-specialist personnel and in rural areas, increasing quality and objectivity of the analysis while simultaneously reducing the labour and need for highly trained specialists.
47.	Hirsch, Jan-Michaél, et al. (författare) Icke-invasiv kontroll av cellförändringar i munslemhinnan 2021 Ingår i: Tandläkartidningen. - Stockholm, Sweden : Sveriges Tandläkarförbund. - 0039-6982. ; :9, s. 48-55 Forskningsöversikt (refereegranskat)
48.	Peskov, Vladimir, et al. (författare) Fundamentals of gas micropattern detectors 2001 Ingår i: arXiv preprint physics/0106016. - Cornell University Library. Tidskriftsartikel (refereegranskat)
49.	Waterton, John C., et al. (författare) Repeatability and reproducibility of longitudinal relaxation rate in 12 small-animal MRI systems 2019 Ingår i: Magnetic Resonance Imaging. - : Elsevier BV. - 1873-5894 .- 0730-725X. ; 59, s. 121-129 Tidskriftsartikel (refereegranskat)abstract Background: Many translational MR biomarkers derive from measurements of the water proton longitudinal relaxation rate R 1 , but evidence for between-site reproducibility of R 1 in small-animal MRI is lacking. Objective: To assess R 1 repeatability and multi-site reproducibility in phantoms for preclinical MRI. Methods: R 1 was measured by saturation recovery in 2% agarose phantoms with five nickel chloride concentrations in 12 magnets at 5 field strengths in 11 centres on two different occasions within 1–13 days. R 1 was analysed in three different regions of interest, giving 360 measurements in total. Root-mean-square repeatability and reproducibility coefficients of variation (CoV) were calculated. Propagation of reproducibility errors into 21 translational MR measurements and biomarkers was estimated. Relaxivities were calculated. Dynamic signal stability was also measured. Results: CoV for day-to-day repeatability (N = 180 regions of interest) was 2.34% and for between-centre reproducibility (N = 9 centres) was 1.43%. Mostly, these do not propagate to biologically significant between-centre error, although a few R 1 -based MR biomarkers were found to be quite sensitive even to such small errors in R 1 , notably in myocardial fibrosis, in white matter, and in oxygen-enhanced MRI. The relaxivity of aqueous Ni 2+ in 2% agarose varied between 0.66 s −1 mM −1 at 3 T and 0.94 s −1 mM −1 at 11.7T. Interpretation: While several factors affect the reproducibility of R 1 -based MR biomarkers measured preclinically, between-centre propagation of errors arising from intrinsic equipment irreproducibility should in most cases be small. However, in a few specific cases exceptional efforts might be required to ensure R 1 -reproducibility.
50.	Ahlander, Britt-Marie, 1954-, et al. (författare) An echo-planar imaging sequence is superior to a steady-state free precession sequence for visual as well as quantitative assessment of cardiac magnetic resonance stress perfusion 2017 Ingår i: Clinical Physiology and Functional Imaging. - : Blackwell Publishing. - 1475-0961 .- 1475-097X. ; 37:1, s. 52-61 Tidskriftsartikel (refereegranskat)abstract BACKGROUND: To assess myocardial perfusion, steady-state free precession cardiac magnetic resonance (SSFP, CMR) was compared with gradient-echo-echo-planar imaging (GRE-EPI) using myocardial perfusion scintigraphy (MPS) as reference.METHODS: Cardiac magnetic resonance perfusion was recorded in 30 patients with SSFP and in another 30 patients with GRE-EPI. Timing and extent of inflow delay to the myocardium was visually assessed. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were calculated. Myocardial scar was visualized with a phase-sensitive inversion recovery sequence (PSIR). All scar positive segments were considered pathologic. In MPS, stress and rest images were used as in clinical reporting. The CMR contrast wash-in slope was calculated and compared with the stress score from the MPS examination. CMR scar, CMR perfusion and MPS were assessed separately by one expert for each method who was blinded to other aspects of the study.RESULTS: Visual assessment of CMR had a sensitivity for the detection of an abnormal MPS at 78% (SSFP) versus 91% (GRE-EPI) and a specificity of 58% (SSFP) versus 84% (GRE-EPI). Kappa statistics for SSFP and MPS was 0·29, for GRE-EPI and MPS 0·72. The ANOVA of CMR perfusion slopes for all segments versus MPS score (four levels based on MPS) had correlation r = 0·64 (SSFP) and r = 0·96 (GRE-EPI). SNR was for normal segments 35·63 ± 11·80 (SSFP) and 17·98 ± 8·31 (GRE-EPI), while CNR was 28·79 ± 10·43 (SSFP) and 13·06 ± 7·61 (GRE-EPI).CONCLUSION: GRE-EPI displayed higher agreement with the MPS results than SSFP despite significantly lower signal intensity, SNR and CNR.

Skapa referenser, mejla, bekava och länka

Länka till träfflistan

Träfflista för sökning "hsv:(ENGINEERING AND TECHNOLOGY) hsv:(Medical Engineering) hsv:(Medical Image Processing) "

Avgränsa träffmängd

År