| 1. |
- Krueger, Martin W., et al.
(författare)
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In-silico modeling of atrial repolarization in normal and atrial fibrillation remodeled state
- 2013
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Ingår i: Medical & Biological Engineering & Computing. - : Springer Science and Business Media LLC. - 0140-0118 .- 1741-0444. ; 51:10, s. 1105-1119
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Tidskriftsartikel (refereegranskat)abstract
- Atrial fibrillation (AF) is the most common cardiac arrhythmia, and the total number of AF patients is constantly increasing. The mechanisms leading to and sustaining AF are not completely understood yet. Heterogeneities in atrial electrophysiology seem to play an important role in this context. Although some heterogeneities have been used in in-silico human atrial modeling studies, they have not been thoroughly investigated. In this study, the original electrophysiological (EP) models of Courtemanche et al., Nygren et al. and Maleckar et al. were adjusted to reproduce action potentials in 13 atrial regions. The parameter sets were validated against experimental action potential duration data and ECG data from patients with AV block. The use of the heterogeneous EP model led to a more synchronized repolarization sequence in a variety of 3D atrial anatomical models. Combination of the heterogeneous EP model with a model of persistent AF-remodeled electrophysiology led to a drastic change in cell electrophysiology. Simulated Ta-waves were significantly shorter under the remodeling. The heterogeneities in cell electrophysiology explain the previously observed Ta-wave effects. The results mark an important step toward the reliable simulation of the atrial repolarization sequence, give a deeper understanding of the mechanism of atrial repolarization and enable further clinical investigations.
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| 2. |
- Qian, Kun, et al.
(författare)
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An eye tracking based virtual reality system for use inside magnetic resonance imaging systems
- 2021
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Patients undergoing Magnetic Resonance Imaging (MRI) often experience anxiety and sometimes distress prior to and during scanning. Here a full MRI compatible virtual reality (VR) system is described and tested with the aim of creating a radically different experience. Potential benefits could accrue from the strong sense of immersion that can be created with VR, which could create sense experiences designed to avoid the perception of being enclosed and could also provide new modes of diversion and interaction that could make even lengthy MRI examinations much less challenging. Most current VR systems rely on head mounted displays combined with head motion tracking to achieve and maintain a visceral sense of a tangible virtual world, but this technology and approach encourages physical motion, which would be unacceptable and could be physically incompatible for MRI. The proposed VR system uses gaze tracking to control and interact with a virtual world. MRI compatible cameras are used to allow real time eye tracking and robust gaze tracking is achieved through an adaptive calibration strategy in which each successive VR interaction initiated by the subject updates the gaze estimation model. A dedicated VR framework has been developed including a rich virtual world and gaze-controlled game content. To aid in achieving immersive experiences physical sensations, including noise, vibration and proprioception associated with patient table movements, have been made congruent with the presented virtual scene. A live video link allows subject-carer interaction, projecting a supportive presence into the virtual world.
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| 3. |
- Ulén, Johannes, et al.
(författare)
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Optimization for Multi-Region Segmentation of Cardiac MRI
- 2011
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Ingår i: Lecture Notes in Computer Science (Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges Second International Workshop, STACOM 2011, Held in Conjunction with MICCAI 2011, Toronto, ON, Canada, September 22, 2011, Revised Selected Papers). - Berlin, Heidelberg : Springer Berlin Heidelberg. - 1611-3349 .- 0302-9743. - 9783642283260 - 9783642283253 ; 7085, s. 129-138
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Konferensbidrag (refereegranskat)abstract
- We introduce a new multi-region model for simultaneous segmentation of the left and right ventricles, myocardium and the left ventricular papillary muscles in MRI. The model enforces geometric constraints such as inclusion and exclusion between the regions, which makes it possible to correctly segment different regions even though the intensity distributions are identical. We efficiently optimize the model using Lagrangian duality which is faster and more memory efficient than current state of the art. As the optimization is based on global techniques, the resulting segmentations are independent of initialization. We evaluate our approach on two benchmarks with competitive results.
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| 4. |
- Zhuang, Xiahai, et al.
(författare)
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Evaluation of algorithms for Multi-Modality Whole Heart Segmentation : An open-access grand challenge.
- 2019
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Ingår i: Medical Image Analysis. - : Elsevier BV. - 1361-8415 .- 1361-8423. ; 58
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Tidskriftsartikel (refereegranskat)abstract
- Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be challenging due to the large variation of the heart shape, and different image qualities of the clinical data. To achieve this goal, an initial set of training data is generally needed for constructing priors or for training. Furthermore, it is difficult to perform comparisons between different methods, largely due to differences in the datasets and evaluation metrics used. This manuscript presents the methodologies and evaluation results for the WHS algorithms selected from the submissions to the Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, in conjunction with MICCAI 2017. The challenge provided 120 three-dimensional cardiac images covering the whole heart, including 60 CT and 60 MRI volumes, all acquired in clinical environments with manual delineation. Ten algorithms for CT data and eleven algorithms for MRI data, submitted from twelve groups, have been evaluated. The results showed that the performance of CT WHS was generally better than that of MRI WHS. The segmentation of the substructures for different categories of patients could present different levels of challenge due to the difference in imaging and variations of heart shapes. The deep learning (DL)-based methods demonstrated great potential, though several of them reported poor results in the blinded evaluation. Their performance could vary greatly across different network structures and training strategies. The conventional algorithms, mainly based on multi-atlas segmentation, demonstrated good performance, though the accuracy and computational efficiency could be limited. The challenge, including provision of the annotated training data and the blinded evaluation for submitted algorithms on the test data, continues as an ongoing benchmarking resource via its homepage (www.sdspeople.fudan.edu.cn/zhuangxiahai/0/mmwhs/).
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