Fast, accurate, and fully automatic segmentation of the right ventricle in short-axis cardiac MRI

被引:58
作者
Ringenberg, Jordan [1 ]
Deo, Makarand [2 ]
Devabhaktuni, Vijay [1 ]
Berenfeld, Omer [3 ]
Boyers, Pamela [4 ]
Gold, Jeffrey [4 ]
机构
[1] Univ Toledo, Coll Engn, Dept EECS, Toledo, OH 43606 USA
[2] Norfolk State Univ, Dept Engn, Norfolk, VA 23504 USA
[3] Univ Michigan, Dept Internal Med, Ctr Arrhythmia Res, Ann Arbor, MI 48109 USA
[4] Univ Toledo, Intetprofess Immers Simulat Ctr, Toledo, OH 43614 USA
关键词
Cardiac MRI; Ventricular segmentation; A priori constraints; Optimal thresholding; Binary difference of Gaussians filter; IMAGES; REGISTRATION; HEART; MODEL;
D O I
10.1016/j.compmedimag.2013.12.011
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
This paper presents a fully automatic method to segment the right ventricle (RV) from short-axis cardiac M. A combination of a novel window-constrained accumulator thresholding technique, binary difference of Gaussian (DoG) filters, optimal thresholding, and morphology are utilized to drive the segmentation. A priori segmentation window constraints are incorporated to guide and refine the process, as well as to ensure appropriate area confinement of the segmentation. Training and testing were performed using a combined 48 patient datasets supplied by the organizers of the MICCAI 2012 right ventricle segmentation challenge, allowing for unbiased evaluations and benchmark comparisons. Marked improvements in speed and accuracy over the top existing methods are demonstrated. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:190 / 201
页数:12
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