Literature DB >> 22481023

Complete valvular heart apparatus model from 4D cardiac CT.

Sasa Grbic1, Razvan Ionasec, Dime Vitanovski, Ingmar Voigt, Yang Wang, Bogdan Georgescu, Nassir Navab, Dorin Comaniciu.   

Abstract

The cardiac valvular apparatus, composed of the aortic, mitral, pulmonary and tricuspid valves, is an essential part of the anatomical, functional and hemodynamic characteristics of the heart and the cardiovascular system as a whole. Valvular heart diseases often involve multiple dysfunctions and require joint assessment and therapy of the valves. In this paper, we propose a complete and modular patient-specific model of the cardiac valvular apparatus estimated from 4D cardiac CT data. A new constrained Multi-linear Shape Model (cMSM), conditioned by anatomical measurements, is introduced to represent the complex spatio-temporal variation of the heart valves. The cMSM is exploited within a learning-based framework to efficiently estimate the patient-specific valve parameters from cine images. Experiments on 64 4D cardiac CT studies demonstrate the performance and clinical potential of the proposed method. Our method enables automatic quantitative evaluation of the complete valvular apparatus based on non-invasive imaging techniques. In conjunction with existent patient-specific chamber models, the presented valvular model enables personalized computation modeling and realistic simulation of the entire cardiac system. Crown
Copyright © 2012. Published by Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22481023     DOI: 10.1016/j.media.2012.02.003

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  11 in total

1.  Automatic estimation of aortic and mitral valve displacements in dynamic CTA with 4D graph-cuts.

Authors:  Juan E Ortuño; Gonzalo Vegas-Sánchez-Ferrero; Juan J Gómez-Valverde; Marcus Y Chen; Andrés Santos; Elliot R McVeigh; María J Ledesma-Carbayo
Journal:  Med Image Anal       Date:  2020-06-06       Impact factor: 8.545

2.  Extraction of open-state mitral valve geometry from CT volumes.

Authors:  Lennart Tautz; Mathias Neugebauer; Markus Hüllebrand; Katharina Vellguth; Franziska Degener; Simon Sündermann; Isaac Wamala; Leonid Goubergrits; Titus Kuehne; Volkmar Falk; Anja Hennemuth
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-08-03       Impact factor: 2.924

3.  Artificial intelligence and automation in valvular heart diseases.

Authors:  Qiang Long; Xiaofeng Ye; Qiang Zhao
Journal:  Cardiol J       Date:  2020-06-22       Impact factor: 2.737

4.  Automatic segmentation of the aortic root in CT angiography of candidate patients for transcatheter aortic valve implantation.

Authors:  M A Elattar; E M Wiegerinck; R N Planken; E Vanbavel; H C van Assen; J Baan; H A Marquering
Journal:  Med Biol Eng Comput       Date:  2014-06-06       Impact factor: 2.602

5.  A framework for designing patient-specific bioprosthetic heart valves using immersogeometric fluid-structure interaction analysis.

Authors:  Fei Xu; Simone Morganti; Rana Zakerzadeh; David Kamensky; Ferdinando Auricchio; Alessandro Reali; Thomas J R Hughes; Michael S Sacks; Ming-Chen Hsu
Journal:  Int J Numer Method Biomed Eng       Date:  2018-01-25       Impact factor: 2.747

Review 6.  Toward patient-specific simulations of cardiac valves: state-of-the-art and future directions.

Authors:  Emiliano Votta; Trung Bao Le; Marco Stevanella; Laura Fusini; Enrico G Caiani; Alberto Redaelli; Fotis Sotiropoulos
Journal:  J Biomech       Date:  2012-11-20       Impact factor: 2.712

Review 7.  Artificial intelligence in cardiovascular CT: Current status and future implications.

Authors:  Andrew Lin; Márton Kolossváry; Manish Motwani; Ivana Išgum; Pál Maurovich-Horvat; Piotr J Slomka; Damini Dey
Journal:  J Cardiovasc Comput Tomogr       Date:  2021-03-22

8.  A geometric model for the human pulmonary valve in its fully open case.

Authors:  Xiaoqin Shen; Lin Bai; Li Cai; Xiaoshan Cao
Journal:  PLoS One       Date:  2018-06-25       Impact factor: 3.240

Review 9.  Artificial intelligence: improving the efficiency of cardiovascular imaging.

Authors:  Andrew Lin; Márton Kolossváry; Ivana Išgum; Pál Maurovich-Horvat; Piotr J Slomka; Damini Dey
Journal:  Expert Rev Med Devices       Date:  2020-06-16       Impact factor: 3.166

10.  Population-based prediction of subject-specific prostate deformation for MR-to-ultrasound image registration.

Authors:  Yipeng Hu; Eli Gibson; Hashim Uddin Ahmed; Caroline M Moore; Mark Emberton; Dean C Barratt
Journal:  Med Image Anal       Date:  2015-10-31       Impact factor: 8.545

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