| 1. |
- Abtahi, Jahan, et al.
(författare)
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Bisphosphonate coating might improve fixation of dental implants in the maxilla: A pilot study
- 2010
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Ingår i: International Journal of Oral and Maxillofacial Surgery. - : Elsevier Science B.V., Amsterdam. - 0901-5027 .- 1399-0020. ; 39:7, s. 673-677
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Tidskriftsartikel (refereegranskat)abstract
- This pilot study evaluates the clinical stability of bisphosphonate-coated dental implants placed using a two-stage surgical procedure in five patients. Each patient received seven regular Brånemark implants, one of which was coated with bisphosphonate in a fibrinogen matrix. The coated implant was inserted where the bone was expected to have the least favourable quality. The level of the marginal bone around each implant was measured by intraoral periapical radiographs and implant stability was recorded using resonance frequency measurements. Frequency values (ISQ) were obtained peroperatively before flap closure and after 6 months at abutment connection. At abutment connection the bisphosphonate-coated implants were removed en bloc in two patients for histological examination. An animal experiment had previously confirmed that gamma-sterilization did not reduce bioactivity of the bisphosphonate coating. In each patient, the bisphosphonate-coated implant showed the largest improvement in ISQ level of all implants. Their values at the start tended to be lower, and the absolute value at 6 months did not differ. No complications occurred with the coated implants. Histology showed no abnormalities. Improvement in ISQ values was an expected effect of the bisphosphonate coating, but could be due to the choice of insertion site. This finding warrants a randomized, blinded study.
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| 2. |
- Ge, Chenjie, 1991, et al.
(författare)
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Enlarged Training Dataset by Pairwise GANs for Molecular-Based Brain Tumor Classification
- 2020
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Ingår i: IEEE Access. - 2169-3536 .- 2169-3536. ; 8:1, s. 22560-22570
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Tidskriftsartikel (refereegranskat)abstract
- This paper addresses issues of brain tumor subtype classification using Magnetic Resonance Images (MRIs) from different scanner modalities like T1 weighted, T1 weighted with contrast-enhanced, T2 weighted and FLAIR images. Currently most available glioma datasets are relatively moderate in size, and often accompanied with incomplete MRIs in different modalities. To tackle the commonly encountered problems of insufficiently large brain tumor datasets and incomplete modality of image for deep learning, we propose to add augmented brain MR images to enlarge the training dataset by employing a pairwise Generative Adversarial Network (GAN) model. The pairwise GAN is able to generate synthetic MRIs across different modalities. To achieve the patient-level diagnostic result, we propose a post-processing strategy to combine the slice-level glioma subtype classification results by majority voting. A two-stage course-to-fine training strategy is proposed to learn the glioma feature using GAN-augmented MRIs followed by real MRIs. To evaluate the effectiveness of the proposed scheme, experiments have been conducted on a brain tumor dataset for classifying glioma molecular subtypes: isocitrate dehydrogenase 1 (IDH1) mutation and IDH1 wild-type. Our results on the dataset have shown good performance (with test accuracy 88.82%). Comparisons with several state-of-the-art methods are also included.
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| 3. |
- Ali, Muhaddisa Barat, 1986, et al.
(författare)
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A novel federated deep learning scheme for glioma and its subtype classification
- 2023
-
Ingår i: Frontiers in Neuroscience. - 1662-4548 .- 1662-453X. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- Background: Deep learning (DL) has shown promising results in molecular-based classification of glioma subtypes from MR images. DL requires a large number of training data for achieving good generalization performance. Since brain tumor datasets are usually small in size, combination of such datasets from different hospitals are needed. Data privacy issue from hospitals often poses a constraint on such a practice. Federated learning (FL) has gained much attention lately as it trains a central DL model without requiring data sharing from different hospitals. Method: We propose a novel 3D FL scheme for glioma and its molecular subtype classification. In the scheme, a slice-based DL classifier, EtFedDyn, is exploited which is an extension of FedDyn, with the key differences on using focal loss cost function to tackle severe class imbalances in the datasets, and on multi-stream network to exploit MRIs in different modalities. By combining EtFedDyn with domain mapping as the pre-processing and 3D scan-based post-processing, the proposed scheme makes 3D brain scan-based classification on datasets from different dataset owners. To examine whether the FL scheme could replace the central learning (CL) one, we then compare the classification performance between the proposed FL and the corresponding CL schemes. Furthermore, detailed empirical-based analysis were also conducted to exam the effect of using domain mapping, 3D scan-based post-processing, different cost functions and different FL schemes. Results: Experiments were done on two case studies: classification of glioma subtypes (IDH mutation and wild-type on TCGA and US datasets in case A) and glioma grades (high/low grade glioma HGG and LGG on MICCAI dataset in case B). The proposed FL scheme has obtained good performance on the test sets (85.46%, 75.56%) for IDH subtypes and (89.28%, 90.72%) for glioma LGG/HGG all averaged on five runs. Comparing with the corresponding CL scheme, the drop in test accuracy from the proposed FL scheme is small (−1.17%, −0.83%), indicating its good potential to replace the CL scheme. Furthermore, the empirically tests have shown that an increased classification test accuracy by applying: domain mapping (0.4%, 1.85%) in case A; focal loss function (1.66%, 3.25%) in case A and (1.19%, 1.85%) in case B; 3D post-processing (2.11%, 2.23%) in case A and (1.81%, 2.39%) in case B and EtFedDyn over FedAvg classifier (1.05%, 1.55%) in case A and (1.23%, 1.81%) in case B with fast convergence, which all contributed to the improvement of overall performance in the proposed FL scheme. Conclusion: The proposed FL scheme is shown to be effective in predicting glioma and its subtypes by using MR images from test sets, with great potential of replacing the conventional CL approaches for training deep networks. This could help hospitals to maintain their data privacy, while using a federated trained classifier with nearly similar performance as that from a centrally trained one. Further detailed experiments have shown that different parts in the proposed 3D FL scheme, such as domain mapping (make datasets more uniform) and post-processing (scan-based classification), are essential.
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| 4. |
- Inci, Kamuran, et al.
(författare)
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Air bubbles are released by thoracic endograft deployment: An in vitro experimental study
- 2016
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Ingår i: SAGE Open Medicine. - : SAGE Publications. - 2050-3121. ; 4
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Embolic stroke is a dreaded complication of thoracic endovascular aortic repair. The prevailing theory about its cause is that particulate debris from atherosclerotic lesions in the aortic wall are dislodged by endovascular instruments and embolize to the brain. An alternative source of embolism might be air trapped in the endograft delivery system. The aim of this experimental study was to determine whether air is released during deployment of a thoracic endograft. Methods: In an experimental benchtop study, eight thoracic endografts (five Medtronic Valiant Thoracic and three Gore TAG) were deployed in a water-filled transparent container drained from air. Endografts were prepared and deployed according to their instructions for use. Deployment was filmed and the volume of air released was collected and measured in a calibrated syringe. Results: Air was released from all the endografts examined. Air volumes ranged from 0.1 to 0.3 mL for Medtronic Valiant Thoracic and from <0.025 to 0.04 mL for Gore TAG. The largest bubbles had a diameter of approximately 3 mm and came from the proximal end of the Medtronic Valiant device. Conclusion: Air bubbles are released from thoracic endografts during deployment. Air embolism may be an alternative cause of stroke during thoracic endovascular aortic repair.
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| 5. |
- Lundh, Torbjörn, 1965, et al.
(författare)
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Torque Devices
- 2018
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Torque devices for navigating a guidewire through a body lumen are disclosed. The devices have a variable speed transmission design, including at least a first transmission region along a first position of the device, and a second transmission region along a second position of the device. The first and second transmission regions have different diameters, thereby allowing rotational control of the guidewire between at least two different stroke angles.
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| 6. |
- Robinson, Yohan, 1977, et al.
(författare)
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AI och framtidens försvarsmedicin
- 2020
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Medicinskt legitimerad personal är, och kommer med stor sannolikhet fortsattatt vara, en knapp resurs inom Försvarsmaktens sjukvårdsorganisation. I denna rapport ges en översikt över pågående och planerade ansatser baserade påartificiell intelligens (AI) inom akutsjukvård med särskild tonvikt på omhändertagandet av traumapatienter, där lösningarna skulle kunna bidra till att Försvarsmakten kan bibehålla sin sjukvårdskapacitet i kritiska lägen. Rapporten är ett resultat av samarbetet mellan FM, FOI, FMV, FHS och KI, och vänder sig i första hand till Försvarsmaktens strategiska ledning.Användningen av AI-teknik i framtida beslutsstöd kan skapa nya möjligheter till avlastning av personal och resurseffektivisering. Tekniken ger möjligheter att i realtid samla in, bearbeta och analysera stora mängder blandadinformation om förbands hälsoläge och fysiska stridsvärde. Bedömning av skadade kan t.ex. göras av triagedrönare och den efterföljande evakueringen kanunderlättas av intelligenta autonoma plattformar. Införandet av AI-system ställer dock vårdgivaren inför svåra etiska och medikolegala överväganden.Försvarsmedicin har en central roll i Försvarsmaktens krigföringsförmåga och för samhällets uthållighet. För att nyttja hela AI-teknikens framfart till Försvarsmaktens nytta måste dess innebörd och konsekvens för försvarsmedicinen förstås. Därför rekommenderar denna studie att Försvarsmaktens framtida satsningar inom AI och autonomi inkluderar den försvarsmedicinska teknikutveckling som är beskriven i denna rapport.
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| 7. |
- Haj-Hosseini, Neda, 1980-, et al.
(författare)
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Early Detection of Oral Potentially Malignant Disorders: A Review on Prospective Screening Methods with Regard to Global Challenges
- 2024
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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
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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.
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| 8. |
- Bondesson, Johan, 1991
(författare)
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Geometric Modeling of Thoracic Aortic Surface Morphology - Implications for Pathophysiology and Clinical Interventions
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Vascular disease risk factors such as hypertension, hyperlipidemia and old age are all results of modern-day lifestyle, and these diseases are getting more and more common. One treatment option for vascular diseases such as aneurysms and dissections is endovascular aortic repair introduced in the early 1990s. This treatment uses tubular fabric covered metallic structures (endografts) that are implanted using a minimally invasive approach and placed to serve as an articial vessel in a damaged portion of the vasculature. To ensure that the interventions are successful, the endograft must be placed in the correct location, and designed to sustain the hostile biological, chemical, and mechanical conditions in the body for many years. This is an interaction that goes both ways, and keeping in mind that the endograft is a foreign object placed in the sensitive vascular system, it is also important that it does not disrupt the native conditions more than necessary. This thesis presents a segmentation and quantication methodology to accurately describe the complex morphology and motion of diseased blood vessels in vivo through a natural and intuitive description of their luminal surfaces. After methodology validation, a series of important clinical applications are performed, all based on non-invasive imaging. Firstly, it is shown that explicit surface curvature quantication is necessary when compared to relying solely on centerline curvature and estimation methods. Secondly, it is shown that endograft malapposition severity can be predicted from preoperative geometric analysis of thoracic aortic surfaces. Thirdly, a multiaxial dynamics analysis of cardiac induced thoracic aortic surface motion shows how thoracic endovascular aortic repair affects the deformations of the dierent portions of the thoracic aorta. Fourthly, the helical propagation pattern of type B aortic dissection is determined, and two distinct modes of chirality are revealed, i.e., achiral and right-handed chiral groups. Finally, the effects of thoracic endovascular aortic repair on helical and cross-sectional morphology of type B dissections are investigated revealing how acuity and chirality affects the alteration due to intraluminal lining with endografts. Thus, the work presented in this thesis contributes by adding knowledge about pathology and pathophysiology through better geometric description of surface conditions of diseased thoracic aortas. This gives clinicians insights to use in their treatment planning and provides more nuanced boundary conditions for endograft manufacturers. Comprehensive knowledge about diseases, better treatment planning, and better devices are all crucial in order to improve the outcomes of performed interventions and ultimately the quality of life for the treated patients.
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| 9. |
- Carlsson, Anna K, 1966, et al.
(författare)
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Rollator related pedestrian single accidents and collision events in Sweden
- 2022
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Ingår i: Traffic Safety Research (TSR). - : Lund University. - 2004-3082. ; 2
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Tidskriftsartikel (refereegranskat)abstract
- Rollators (four-wheel walkers in USA; zimmer frames in UK) are commonly used as mobility aids for the elderly and people with a variety of disabilities. Pedestrian rollator users are a sub-group of Vulnerable Road Users (VRUs), although this group is rarely recognised in traffic safety contexts. The aim of this study is to extract and analyse rollator related pedestrian accident and injury data in Sweden. The results will provide valuable insight into the risks and obstacles rollator users are exposed to in the traffic environment and may in the long term contribute to improving the mobility of this group. The current study is based on data from 2,020 accidents involving 2,305 persons extracted from the Swedish Traffic Accident Data Acquisition (STRADA) database. For consistency reasons, a subset of data (N = 745) was analysed in order to investigate the development of accidents over a period of 10 years. Thereafter, each accident in the whole data set was registered as either single or collision. The results show that the number of rollator accidents in Sweden increased by approximately 80% during 2007–2016. Females dominate the injury statistics of single accidents, collisions, as well as fatal outcome, which may be due to exposure and/or differences in physical characteristics. Single accidents are much more common than collisions (n=1,668 and n=352, respectively) and the injury consequences are at least as serious. Data from the present study have revealed that the frequency of minor injuries (ISS 1–3) is 4.3 times, moderate (ISS 4–8) 6.0 times and serious injuries (ISS 9–15) 8.9 times higher in single accidents than in collisions. Fatal injuries are, however, more common in collision events (33 in comparison to 8). The vast majority of single accidents (99%) was due to falls. Many of the single accidents (29%) were caused by ground level differences (typically a curb) or due to surface conditions (19%). Collisions involved cars, trucks or buses in 91% of cases, occurring predominantly in car parks (31%) and on (zebra) crossings (30%). In 54% of cases the vehicles reversed into the rollator. Abbreviated Injury Scale (AIS) 3+ injuries were dominated by head (36%) and torso (33%) injuries in collision events, and hip fractures (71%) in single accidents. The present study shows that further research into rollator user related accidents, both single accidents and collision events, is required. In order to introduce appropriate measures, future work should follow up on accident and injury developments and further improve the quality of mobility aid related accident data in general. Improved stability and design, proper training programmes, effective maintenance services, development of a supporting infrastructure would contribute to increased safety for rollator users.
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| 10. |
- Ge, Chenjie, 1991, et al.
(författare)
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Cross-Modality Augmentation of Brain Mr Images Using a Novel Pairwise Generative Adversarial Network for Enhanced Glioma Classification
- 2019
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Ingår i: Proceedings - International Conference on Image Processing, ICIP. - 1522-4880.
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Konferensbidrag (refereegranskat)abstract
- © 2019 IEEE. Brain Magnetic Resonance Images (MRIs) are commonly used for tumor diagnosis. Machine learning for brain tumor characterization often uses MRIs from many modalities (e.g., T1-MRI, Enhanced-T1-MRI, T2-MRI and FLAIR). This paper tackles two issues that may impact brain tumor characterization performance from deep learning: insufficiently large training dataset, and incomplete collection of MRIs from different modalities. We propose a novel pairwise generative adversarial network (GAN) architecture for generating synthetic brain MRIs in missing modalities by using existing MRIs in other modalities. By improving the training dataset, we aim to mitigate the overfitting and improve the deep learning performance. Main contributions of the paper include: (a) propose a pairwise generative adversarial network (GAN) for brain image augmentation via cross-modality image generation; (b) propose a training strategy to enhance the glioma classification performance, where GAN-augmented images are used for pre-training, followed by refined-training using real brain MRIs; (c) demonstrate the proposed method through tests and comparisons of glioma classifiers that are trained from mixing real and GAN synthetic data, as well as from real data only. Experiments were conducted on an open TCGA dataset, containing 167 subjects for classifying IDH genotypes (mutation or wild-type). Test results from two experimental settings have both provided supports to the proposed method, where glioma classification performance has consistently improved by using mixed real and augmented data (test accuracy 81.03%, with 2.57% improvement).
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