Literature DB >> 21216179

A review of segmentation methods in short axis cardiac MR images.

Caroline Petitjean1, Jean-Nicolas Dacher.   

Abstract

For the last 15 years, Magnetic Resonance Imaging (MRI) has become a reference examination for cardiac morphology, function and perfusion in humans. Yet, due to the characteristics of cardiac MR images and to the great variability of the images among patients, the problem of heart cavities segmentation in MRI is still open. This paper is a review of fully and semi-automated methods performing segmentation in short axis images using a cardiac cine MRI sequence. Medical background and specific segmentation difficulties associated to these images are presented. For this particularly complex segmentation task, prior knowledge is required. We thus propose an original categorization for cardiac segmentation methods, with a special emphasis on what level of external information is required (weak or strong) and how it is used to constrain segmentation. After reviewing method principles and analyzing segmentation results, we conclude with a discussion and future trends in this field regarding methodological and medical issues.
Copyright © 2010 Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 21216179     DOI: 10.1016/j.media.2010.12.004

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


  103 in total

Review 1.  Principles and methods for automatic and semi-automatic tissue segmentation in MRI data.

Authors:  Lei Wang; Teodora Chitiboi; Hans Meine; Matthias Günther; Horst K Hahn
Journal:  MAGMA       Date:  2016-01-11       Impact factor: 2.310

2.  Semiautomatic three-dimensional CT ventricular volumetry in patients with congenital heart disease: agreement between two methods with different user interaction.

Authors:  Hyun Woo Goo; Sang-Hyub Park
Journal:  Int J Cardiovasc Imaging       Date:  2015-08-29       Impact factor: 2.357

3.  Automatic functional analysis of left ventricle in cardiac cine MRI.

Authors:  Ying-Li Lu; Kim A Connelly; Alexander J Dick; Graham A Wright; Perry E Radau
Journal:  Quant Imaging Med Surg       Date:  2013-08

4.  4D statistical shape modeling of the left ventricle in cardiac MR images.

Authors:  Shahrooz Faghih Roohi; Reza Aghaeizadeh Zoroofi
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-08-15       Impact factor: 2.924

5.  Image-based left ventricular shape analysis for sudden cardiac death risk stratification.

Authors:  Fijoy Vadakkumpadan; Natalia Trayanova; Katherine C Wu
Journal:  Heart Rhythm       Date:  2014-05-20       Impact factor: 6.343

6.  Diagnostic accuracy and variability of three semi-quantitative methods for assessing right ventricular systolic function from cardiac MRI in patients with acquired heart disease.

Authors:  Jérôme Caudron; Jeannette Fares; Pierre-Hugues Vivier; Valentin Lefebvre; Caroline Petitjean; Jean-Nicolas Dacher
Journal:  Eur Radiol       Date:  2011-05-26       Impact factor: 5.315

7.  Left Ventricle Segmentation and Quantification from Cardiac Cine MR Images via Multi-task Learning.

Authors:  Shusil Dangi; Ziv Yaniv; Cristian A Linte
Journal:  Stat Atlases Comput Models Heart       Date:  2019-02-14

8.  Interactive MRI Segmentation with Controlled Active Vision.

Authors:  Peter Karasev; Ivan Kolesov; Karol Chudy; Grant Muller; John Xerogeanes; Allen Tannenbaum
Journal:  Proc IEEE Conf Decis Control       Date:  2011

9.  A collaborative resource to build consensus for automated left ventricular segmentation of cardiac MR images.

Authors:  Avan Suinesiaputra; Brett R Cowan; Ahmed O Al-Agamy; Mustafa A Elattar; Nicholas Ayache; Ahmed S Fahmy; Ayman M Khalifa; Pau Medrano-Gracia; Marie-Pierre Jolly; Alan H Kadish; Daniel C Lee; Ján Margeta; Simon K Warfield; Alistair A Young
Journal:  Med Image Anal       Date:  2013-09-13       Impact factor: 8.545

Review 10.  Challenges of cardiac image analysis in large-scale population-based studies.

Authors:  Pau Medrano-Gracia; Brett R Cowan; Avan Suinesiaputra; Alistair A Young
Journal:  Curr Cardiol Rep       Date:  2015-03       Impact factor: 2.931

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