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Titlebook: Computational Biomechanics for Medicine; Challenges and Solut Adam Wittek,Magdalena Kobielarz,Karol Miller Conference proceedings 2024 The

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书目名称Computational Biomechanics for Medicine
副标题Challenges and Solut
编辑Adam Wittek,Magdalena Kobielarz,Karol Miller
视频video
概述Offers methods and applications of computational biomechanics in medical image analysis.Presents methods of computational biomechanics for computer-assisted therapy.Provides peer-reviewed contribution
丛书名称Lecture Notes in Bioengineering
图书封面Titlebook: Computational Biomechanics for Medicine; Challenges and Solut Adam Wittek,Magdalena Kobielarz,Karol Miller Conference proceedings 2024 The
描述.This book presents peer-reviewed contributions from the MICCAI 2023 Computational Biomechanics for Medicine CBM XVIII Workshop held in conjunction with the 26th International MICCAI Conference. The content focuses on applications of computational biomechanics to computer-integrated medicine, which includes medical image computing, application of machine learning in image analysis and biomechanics, atlas based biomechanical simulations, novel algorithms of computational biomechanics and experimental methods for analysis of disease and injury mechanisms. ..The book details state-of-the-art progress in the above fields to researchers, students, and professionals..
出版日期Conference proceedings 2024
关键词Physics-based Medical Image Analysis; Computer-Integrated Medicine; Biomechanics; Conference Proceeding
版次1
doihttps://doi.org/10.1007/978-3-031-64632-4
isbn_softcover978-3-031-64634-8
isbn_ebook978-3-031-64632-4Series ISSN 2195-271X Series E-ISSN 2195-2728
issn_series 2195-271X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Lecture Notes in Bioengineeringhttp://image.papertrans.cn/d/image/242244.jpg
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https://doi.org/10.1007/978-3-031-64632-4Physics-based Medical Image Analysis; Computer-Integrated Medicine; Biomechanics; Conference Proceeding
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Aktien-, Zins- und Währungsderivateanalysis of biomedical imaging data. Development, validation and continuous refinement of AI tools requires easy access to large, high quality, annotated datasets, which are both representative and diverse. The National Cancer Institute (NCI) Imaging Data Commons (IDC) hosts large and diverse public
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https://doi.org/10.1007/978-3-658-28612-5ry has a negligible impact on the output of the simulation. In this work, we develop a novel method for describing the geometric uncertainty in image-derived models and use a naive method for subsequently quantifying a simulation’s sensitivity to that uncertainty. A Gaussian random field is construc
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Aktien-, Zins- und Währungsderivateintroduces a method for creating a high-quality hexahedral mesh using the Open Anatomy Project‘s brain atlas. Our atlas-based FE hexahedral mesh of the brain mitigates potential inaccuracies and uncertainties due to segmentation—a process that often requires input of an inexperienced analyst. It acc
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