WebDec 21, 2024 · Experiments from the MyoPS2024 challenge dataset show that our framework can achieve promising performance for myocardial scar and edema … WebFeb 7, 2024 · Myocardial pathology segmentation (MyoPS) is critical for the risk stratification and treatment planning of myocardial infarction (MI). Multi-sequence cardiac magnetic resonance (MS-CMR) images can provide valuable information.
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GitHub - chfc-cmi/miccai2024-myops
http://www.sdspeople.fudan.edu.cn/zhuangxiahai/0/myops20/ The method is detailed in the paper, and it won the 1st place of MyoPS 2024. Our code is based on PyMIC, a pytorch-based toolkit for medical image computing with deep learning, that is lightweight and easy to use, and nnUNet, a self-adaptive segmentation method for medical images. See more Our solution is a coarse-to-fine method. PyMIC and nnUNetare used in the coarse and fine stages, respectively. In the coarse segmentation stage, we use 2D U-Net to segment there foreground classes: complete ring-shaped … See more This code depends on Pytorch, PyMIC, GeodisTK and nnUNet.To install PyMIC and GeodisTK, run: To use nnUNet, Download nnUNet, and put them in the ProjectDir such as /mnt/data1/swzhai/projects/MyoPS2024.Other … See more In the fine segmentation stage, we use nnUNet to segment all the classes. This section is highly dependent on nnUNet, so make sure that you have some basic experience of using nnUNetbefore you do the following … See more WebMYOPS2024 challenge1 for the design of MyoPS methods [22]. A common limitation of current DL-based MyoPS methods is that they only can process pre-aligned MS-CMR images [21], [23], [24]. Meanwhile, the only available public MS-CMR dataset (MYOPS2024 challenge dataset) for MyoPS has been pre-aligned prior to release. In clinical applications, buffalo ridge mobile home park