Literature DB >> 20665801

Automated segmentation of myocardial scar in late enhancement MRI using combined intensity and spatial information.

Qian Tao1, Julien Milles, Katja Zeppenfeld, Hildo J Lamb, Jeroen J Bax, Johan H C Reiber, Rob J van der Geest.   

Abstract

Accurate assessment of the size and distribution of a myocardial infarction (MI) from late gadolinium enhancement (LGE) MRI is of significant prognostic value for postinfarction patients. In this paper, an automatic MI identification method combining both intensity and spatial information is presented in a clear framework of (i) initialization, (ii) false acceptance removal, and (iii) false rejection removal. The method was validated on LGE MR images of 20 chronic postinfarction patients, using manually traced MI contours from two independent observers as reference. Good agreement was observed between automatic and manual MI identification. Validation results showed that the average Dice indices, which describe the percentage of overlap between two regions, were 0.83 +/- 0.07 and 0.79 +/- 0.08 between the automatic identification and the manual tracing from observer 1 and observer 2, and the errors in estimated infarct percentage were 0.0 +/- 1.9% and 3.8 +/- 4.7% compared with observer 1 and observer 2. The difference between the automatic method and manual tracing is in the order of interobserver variation. In conclusion, the developed automatic method is accurate and robust in MI delineation, providing an objective tool for quantitative assessment of MI in LGE MR imaging.

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Year:  2010        PMID: 20665801     DOI: 10.1002/mrm.22422

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  19 in total

1.  New automated Markov-Gibbs random field based framework for myocardial wall viability quantification on agent enhanced cardiac magnetic resonance images.

Authors:  Ahmed Elnakib; Garth M Beache; Georgy Gimel'farb; Ayman El-Baz
Journal:  Int J Cardiovasc Imaging       Date:  2011-12-09       Impact factor: 2.357

2.  Preprocedural magnetic resonance imaging for image-guided catheter ablation of scar-related ventricular tachycardia.

Authors:  Qian Tao; Sebastiaan R D Piers; Hildo J Lamb; Katja Zeppenfeld; Rob J van der Geest
Journal:  Int J Cardiovasc Imaging       Date:  2014-10-24       Impact factor: 2.357

3.  Automated quantification of myocardial infarction using graph cuts on contrast delayed enhanced magnetic resonance images.

Authors:  Yingli Lu; Yuesong Yang; Kim A Connelly; Graham A Wright; Perry E Radau
Journal:  Quant Imaging Med Surg       Date:  2012-06

Review 4.  Cardiac imaging: working towards fully-automated machine analysis & interpretation.

Authors:  Piotr J Slomka; Damini Dey; Arkadiusz Sitek; Manish Motwani; Daniel S Berman; Guido Germano
Journal:  Expert Rev Med Devices       Date:  2017-03       Impact factor: 3.166

5.  Myocardial scar identification based on analysis of Look-Locker and 3D late gadolinium enhanced MRI.

Authors:  Qian Tao; Hildo J Lamb; Katja Zeppenfeld; Rob J van der Geest
Journal:  Int J Cardiovasc Imaging       Date:  2014-03-19       Impact factor: 2.357

6.  Myocardium segmentation from DE MRI with guided random walks and sparse shape representation.

Authors:  Jie Liu; Xiahai Zhuang; Hongzhi Xie; Shuyang Zhang; Lixu Gu
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-07-07       Impact factor: 2.924

7.  Pre to Intraoperative Data Fusion Framework for Multimodal Characterization of Myocardial Scar Tissue.

Authors:  Antonio R Porras; Gemma Piella; Antonio Berruezo; Juan Fernández-Armenta; Alejandro F Frangi
Journal:  IEEE J Transl Eng Health Med       Date:  2014-09-04       Impact factor: 3.316

8.  Is Otsu thresholding the answer to reproducible quantification of left atrial scar from late gadolinium-enhancement MRI?

Authors:  Suvai Gunasekaran; Daniel Kim
Journal:  J Cardiovasc Electrophysiol       Date:  2020-09-21

9.  Automatic classification of scar tissue in late gadolinium enhancement cardiac MRI for the assessment of left-atrial wall injury after radiofrequency ablation.

Authors:  Daniel Perry; Alan Morris; Nathan Burgon; Christopher McGann; Robert Macleod; Joshua Cates
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2012-02-23

10.  Myocardial Infarct Segmentation From Magnetic Resonance Images for Personalized Modeling of Cardiac Electrophysiology.

Authors:  Natalia A Trayanova; Fijoy Vadakkumpadan; Eranga Ukwatta; Hermenegild Arevalo; Kristina Li; Jing Yuan; Wu Qiu; Peter Malamas; Katherine C Wu
Journal:  IEEE Trans Med Imaging       Date:  2015-12-25       Impact factor: 10.048

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