DAEFormer
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xmindflow
[MICCAI 2023] DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation
Dear author,： I have read your article on DAEFormer and tested the Synapse dataset using the weights you provided. The final data is consistent with what you proposed in the...
Hello Author, recently I have been doing research on medical image segmentation. For the dae article you wrote, I have the following doubts about the training strategy code for training...
Hi @rezazad68 I hope you have a great last week of the year! Can you explain your implemented dice loss: ``` def _dice_loss(self, score, target): target = target.float() smooth =...
AttributeError: 'Delaunay' object has no attribute 'vertices' This occurs in all my runs.
请问多器官分割可视化代码可以分享一下吗？（Can you share the visualization code for multi organ segmentation?）
hello author can you explain how to run the code. This will help me a lot. thank you
Hello author, how should I modify the code to reproduce the skip-connection =0,1,2,3 in your paper and get the corresponding dice
Hello, thanks for your great work on the multi-organ segmentation task. I am currently working on the full-body segmentation task as well. My task is to use PET/CT images and...
Hello, thank you very much for coming up with DAEFormer, very innovative. Now DAEFormer is a two-dimensional level [B,C,H,W], but when the data is one-dimensional data [B,C,H], how to use...
