Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images
Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images
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DOI：
10.1016/j.media.2016.01.004
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发表时间：
2016-05-01
影响因子：
10.9
通讯作者：
Rhode, Kawal
中科院分区：
文献类型：
--
作者：
Karim, Rashed;Bhagirath, Pranav;Rhode, Kawal
研究表明，晚期钆增强（LGE）心血管磁共振（CMR）成像指导心肌梗死后遗症（如室性心动过速和心力衰竭）患者治疗的可行性。这些进展的临床实施需要对梗死区域进行可重复和可靠的分割。将新的左心室（LV）梗死分割算法与现有算法进行比较具有挑战性。为了便于比较，非常需要使用评估策略对数据集进行基准测试。这篇手稿提出了一个基准评估框架，为未来的算法，从LGE CMR的左室分割梗死。图像数据库包括从两个独立的成像中心获得的30张人类和猪的LGE CMR图像。利用最大似然估计得到了所有数据的一致基真值。在基准测试框架上测试了六种广泛使用的固定阈值方法和五种新开发的算法，结果表明，除了全宽度半最大值（FWHM）固定阈值方法外，这些算法比大多数n-SD固定阈值方法与共识基础真有更好的重叠。在这项工作中，展示了固定阈值方法的一些缺陷。基准评估框架是这项工作的一个贡献，可用于测试和基准测试未来的算法，以检测和量化左室LGE CMR图像中的梗死。数据集、实地真相和评估代码已通过以下网站公开：https://www.cardiacatlas.org/web/guest/challenges。(C) 2016年作者。Elsevier B.V.出版
Studies have demonstrated the feasibility of late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging for guiding the management of patients with sequelae to myocardial infarction, such as ventricular tachycardia and heart failure. Clinical implementation of these developments necessitates a reproducible and reliable segmentation of the infarcted regions. It is challenging to compare new algorithms for infarct segmentation in the left ventricle (LV) with existing algorithms. Benchmarking datasets with evaluation strategies are much needed to facilitate comparison. This manuscript presents a benchmarking evaluation framework for future algorithms that segment infarct from LGE CMR of the LV. The image database consists of 30 LGE CMR images of both humans and pigs that were acquired from two separate imaging centres. A consensus ground truth was obtained for all data using maximum likelihood estimation.Six widely-used fixed-thresholding methods and five recently developed algorithms are tested on the benchmarking framework, Results demonstrate that the algorithms have better overlap with the consensus ground truth than most of the n-SD fixed-thresholding methods, with the exception of the Full Width -at-Half-Maximum (FWHM) fixed-thresholding method. Some of the pitfalls of fixed thresholding methods are demonstrated in this work. The benchmarking evaluation framework, which is a contribution of this work, can be used to test and benchmark future algorithms that detect and quantify infarct in LGE CMR images of the LV. The datasets, ground truth and evaluation code have been made publicly available through the website: https://www.cardiacatlas.org/web/guest/challenges. (C) 2016 The Authors. Published by Elsevier B.V.