Mar 19, 2024 · We propose a comprehensive scribble supervision benchmark consisting of seven datasets covering a diverse set of anatomies and pathologies imaged with varying ...
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Mar 19, 2024 · We propose a comprehensive scribble supervision benchmark consisting of seven datasets covering a diverse set of anatomies and pathologies imaged with varying ...
This work proposes a comprehensive scribble supervision benchmark consisting of seven datasets covering a diverse set of anatomies and pathologies imaged ...
Scribble supervision with partial losses enhances state-of-the-art segmentation methods for efficient 3D medical image annotation.
A new framework for scribble learning-based medical image segmentation, which is composed of mix augmentation and cycle consistency and thus is referred to as ...
The ignore label can be used to mark regions that should be ignored by nnU-Net. This can be used to learn from images where only sparse annotations are ...
论文提出了一个全面的scribble标注医学图像分割基准，包括七个数据集，涵盖了不同的解剖结构和病理学，使用了nnU-Net进行评估。论文还开源了代码和scribble基准测试套件。该 ...
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Embarrassingly Simple Scribble Supervision for 3D Medical Segmentation. K Gotkowski, C Lüth, PF Jäger, S Ziegler, L Krämer, S Denner, S Xiao, ... arXiv ...
Embarrassingly Simple Scribble Supervision for 3D Medical Segmentation. K. Gotkowski, C. Lüth, P. Jäger, S. Ziegler, L. Krämer, S. Denner, S. Xiao, N. Disch ...
Embarrassingly Simple Scribble Supervision for 3D Medical Segmentation. K Gotkowski, C Lüth, PF Jäger, S Ziegler, L Krämer, S Denner, S Xiao, ... arXiv ...