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Found 3 papers, 2 papers with code
U-Net v2: Rethinking the Skip Connections of U-Net for Medical Image Segmentation
We evaluate our method on several public medical image segmentation datasets for skin lesion segmentation and polyp segmentation, and the experimental results demonstrate the segmentation accuracy of our new method over state-of-the-art methods, while preserving memory and computational efficiency.
PHG-Net: Persistent Homology Guided Medical Image Classification
The PH module is lightweight and capable of integrating topological features into any CNN or Transformer architectures in an end-to-end fashion.
Keep Your Friends Close & Enemies Farther: Debiasing Contrastive Learning with Spatial Priors in 3D Radiology Images
Understanding of spatial attributes is central to effective 3D radiology image analysis where crop-based learning is the de facto standard.
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