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Titlebook: Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges; 7th International Wo Tommaso Mansi,Kristin McL

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發(fā)表于 2025-3-21 18:44:53 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges
副標(biāo)題7th International Wo
編輯Tommaso Mansi,Kristin McLeod,Alistair Young
視頻videohttp://file.papertrans.cn/877/876373/876373.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges; 7th International Wo Tommaso Mansi,Kristin McL
描述.This book constitutes the thoroughly refereed post-workshop proceedings of the 7th International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges. 7th International Workshop, STACOM 2016, Held in conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected papers..The 24 revised full workshop papers were carefully reviewed and selected from 32 submissions. The papers cover a wide range of topics such as cardiac image processing; atlas construction, statistical modelling of cardiac function across different patient populations; cardiac mapping, cardiac computational physiology; model customization; image-based modelling and image-guided interventional procedures; atlas based functional analysis, ontological schemata for data and results; integrated functional and structural analyses; pre-clinical and clinical applicability of the methods described..
出版日期Conference proceedings 2017
關(guān)鍵詞angiography; cardiac imaging; dynamic programming; infarct diagnosis; modeling; cardiac computed tomograp
版次1
doihttps://doi.org/10.1007/978-3-319-52718-5
isbn_softcover978-3-319-52717-8
isbn_ebook978-3-319-52718-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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Phase-Based Registration of Cardiac Tagged MR Images by Incorporating Anatomical Constraints, we found that the constraint improved both longitudinal and circumferential strains accuracies; (2) on 15 healthy volunteers, the proposed method achieved better tracking accuracy compared to three state-of-the-art methods; (3) on one patient dataset, we show that our method is able to distinguish the infarcted segments from the normal ones.
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Image-Based Real-Time Motion Gating of 3D Cardiac Ultrasound Imagesd gating of live images. We have developed a novel and potentially clinically useful real-time three-dimensional (3D) cardiac motion gating technique that facilitates and supports 3D US-guided procedures. Our proposed real-time 3D-Masked-PCA technique uses the Principal Component Analysis (PCA) stat
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Novel Framework to Integrate Real-Time MR-Guided EP Data with T1 Mapping-Based Computational Heart Mially lethal scar-related arrhythmia. Furthermore, although cardiac MR can provide excellent structural information (i.e., anatomy and scar), these catheter-based procedures have limited electrical information due to sparse electrical maps recorded from endocardial surfaces. In this paper, we propos
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Left Atrial Appendage Segmentation Based on Ranking 2-D Segmentation Proposalsy help doctors diagnose thrombosis and plan LAA closure surgery. Considering large anatomical variations of the LAA, we present a non-model based semi-automated approach for LAA segmentation on CTA data. The method requires only manual selection of four fiducial points to obtain the bounding box for
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Phase-Based Registration of Cardiac Tagged MR Images by Incorporating Anatomical Constraintsroving the motion/strain quantification from tagged MR images. The “tag number constant” concept used in Gabor-based non-tracking methods is integrated into a recent phase-based registration framework. We evaluated our method on both synthetic and real data: (1) on a synthetic data of a normal heart
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