@Article{LeiLi2023,
author="Lei Li
and Fuping Wu
and Sihan Wang
and Xinzhe Luo
and Carlos Martin Isla
and Shuwei Zhai
and Jianpeng Zhang
and Yanfei Liu
and Zhen Zhang
and Markus J. Ankenbrand
and Haochuan Jiang
and Xiaoran Zhang
and Linhong Wang
and Tewodros Weldebirhan Arega
and Elif Altunok
and Zhou Zhao
and Feiyan Li
and Jun Ma
and Xiaoping Yang
and Elodie Puybareau
and Ilkay Oksuz
and Stephanie Bricq
and Weisheng Li
and Kumaradevan Punithakumar
and Sotirios A. Tsaftaris
and Laura M. Schreiber
and Mingjing Yang
and Guocai Liu
and Yong Xia
and Guotai Wang
and Sergio Escalera
and Xiahai Zhuag",
title="MyoPS: A benchmark of myocardial pathology segmentation combining three-sequence cardiac magnetic resonance images",
journal="Medical Image Analysis",
year="2023",
volume="87",
pages="102808",
abstract="Assessment of myocardial viability is essential in diagnosis and treatment management of patients suffering from myocardial infarction, and classification of pathology on the myocardium is the key to this assessment. This work defines a new task of medical image analysis, i.e., to perform myocardial pathology segmentation (MyoPS) combining three-sequence cardiac magnetic resonance (CMR) images, which was first proposed in the MyoPS challenge, in conjunction with MICCAI 2020. Note that MyoPS refers to both myocardial pathology segmentation and the challenge in this paper. The challenge provided 45 paired and pre-aligned CMR images, allowing algorithms to combine the complementary information from the three CMR sequences for pathology segmentation. In this article, we provide details of the challenge, survey the works from fifteen participants and interpret their methods according to five aspects, i.e., preprocessing, data augmentation, learning strategy, model architecture and post-processing. In addition, we analyze the results with respect to different factors, in order to examine the key obstacles and explore the potential of solutions, as well as to provide a benchmark for future research. The average Dice scores of submitted algorithms were and for myocardial scars and edema, respectively. We conclude that while promising results have been reported, the research is still in the early stage, and more in-depth exploration is needed before a successful application to the clinics. MyoPS data and evaluation tool continue to be publicly available upon registration via its homepage (www.sdspeople.fudan.edu.cn/zhuangxiahai/0/myops20/).",
optnote="HUPBA",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3878), last updated on Mon, 22 Jan 2024 11:24:08 +0100",
opturl="https://www.sciencedirect.com/science/article/abs/pii/S1361841523000695"
}