| 1. |
- Broman, Mikael, et al.
(författare)
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Recirculation during veno-venous extra-corporeal membrane oxygenation - a simulation study
- 2015
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Ingår i: International Journal of Artificial Organs. - : SAGE Publications. - 0391-3988 .- 1724-6040. ; 38:1, s. 23-30
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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.
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| 2. |
- Mendrik, AM, et al.
(författare)
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MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans
- 2015
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Ingår i: Computational Intelligence and Neuroscience. - : Hindawi Publishing Corporation. - 1687-5265 .- 1687-5273. ; 2015
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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.
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| 3. |
- Grishenkov, Dmitry, 1983-, et al.
(författare)
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In search of the optimal ultrasound heart perfusion imaging platform
- 2015
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Ingår i: Journal of ultrasound in medicine. - : Wiley. - 0278-4297 .- 1550-9613. ; 34:9, s. 1599-1605
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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.
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| 4. |
- Kothapalli, Veera Venkata Satya Naray, 1985-, et al.
(författare)
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Unique pumping-out fracturing mechanism of a polymer-shelled contrast agent : An acoustic characterization and optical visualization
- 2014
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Ingår i: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control. - 0885-3010 .- 1525-8955. ; 62:3, s. 451-462
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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.
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| 5. |
- Lidayová, Kristína, et al.
(författare)
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Fast vascular skeleton extraction algorithm
- 2016
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Ingår i: Pattern Recognition Letters. - : Elsevier. - 0167-8655 .- 1872-7344. ; 76, s. 67-75
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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%.
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| 6. |
- Marlevi, David
(författare)
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Non-invasive imaging for improved cardiovascular diagnostics : Shear wave elastography, relative pressure estimation, and tomographic reconstruction
- 2019
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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.
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| 7. |
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| 8. |
- Shakya, Snehlata, et al.
(författare)
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Multi-fiber estimation and tractography for diffusion mri using mixture of non-central wishart distributions
- 2017
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Ingår i: 2017 Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2017. - : Eurographics Association. - 9783038680369 ; , s. 119-123
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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.
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| 9. |
- Wang, Chunliang, 1980-, et al.
(författare)
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CT scan range estimation using multiple body parts detection : let PACS learn the CT image content
- 2016
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Ingår i: International Journal of Computer Assisted Radiology and Surgery. - : Springer. - 1861-6410 .- 1861-6429. ; 11:2, s. 317-325
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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.
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| 10. |
- Wang, Chunliang, 1980-, et al.
(författare)
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Fast level-set based image segmentation using coherent propagation
- 2014
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Ingår i: Medical physics (Lancaster). - : John Wiley and Sons Ltd. - 0094-2405. ; 41:7
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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.
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