boundary-loss:官方代码“边界高度失衡导致的边界丢失”,在MIDL 2019上获得最佳论文奖亚军。MedIA的扩展版本,第67卷,2021年1月-源码

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边界损失 官方存储库,,在上获得最佳论文奖亚军。 谈话记录可。 期刊扩展已经发表在《。 该代码已简化并更新为最新的Python和Pytorch版本。 除了原始的ISLES和WMH数据集,我们还在多类设置(ACDC数据集)中包含一个工作示例,其中边界损失可以作为独立损失使用。 目录 用法 扩展到3D 自动化 数据方案 资料集 结果 很酷的把戏 多类设置 经常问的问题 损失可以为负吗? 我需要归一化距离图吗? 其他使用边界损失的论文 要求(PyTorch) 核心实现(将边界损耗集成到您自己的代码中): python3.5 + pytorch 1.0+ scipy(任何版本) 要重现我们的实验,请执行以下操作: python3.9 + 火炬1.7+ nibabel(仅在切片3D卷时) 西皮 NumPy Matplotlib Scikit图片 sh 其他框架

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