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Titlebook: Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges; 5th International Wo Oscar Camara,Tommaso Mans

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发表于 2025-3-21 16:10:25 | 显示全部楼层 |阅读模式
书目名称Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges
副标题5th International Wo
编辑Oscar Camara,Tommaso Mansi,Alistair Young
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges; 5th International Wo Oscar Camara,Tommaso Mans
描述This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2014, held in conjunction with MICCAI 2014, in Boston, MA, USA, in September 2014. The 30 revised full papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics such as sections on cardiac image processing; atlas construction; statistical modelling of cardiac function across different patient populations; cardiac mapping; cardiac computational physiology; model customization; atlas based functional analysis; ontological schemata for data and results; integrated functional and structural analyses; as well as the pre-clinical and clinical applicability of these methods.
出版日期Conference proceedings 2015
关键词Applied Computing; Cardiac image analysis; Health informatics; Image processing; Image registration; LV g
版次1
doihttps://doi.org/10.1007/978-3-319-14678-2
isbn_softcover978-3-319-14677-5
isbn_ebook978-3-319-14678-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2015
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Left Ventricular Diastolic and Systolic Material Property Estimation from Image Datalic pressure. These methods were tested in four normal dogs using the data provided for the LV mechanics challenge [2]. The resulting end-diastolic and end-systolic geometry from the simulation were compared with measured image data.
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Identifying Myocardial Mechanical Properties from MRI Using an Orthotropic Constitutive Modeldels to end-diastolic image data. Contractile tension was then estimated by comparing LV model predictions to the end-systolic image data. Personalised models of this kind can be used to predict the 3D deformation and regional stress distributions throughout the LV wall during the entire cardiac cyc
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