guo-stone / mambamorph Goto Github PK
View Code? Open in Web Editor NEWMambaMorph: a Mamba-based Framework for Medical MR-CT Deformable Registration
License: MIT License
MambaMorph: a Mamba-based Framework for Medical MR-CT Deformable Registration
License: MIT License
感谢作者的工作贡献,我遇到了一个问题,我在训练完成VoxelMorph、TransMorph、mm-feat后,进行test,3个模型的DICE结果均为62.42±3.29,这让我很困惑,也就是说形变场没有形变能力,我打印了测试中的扭曲后的标签(warped_label)和原标签(src_label)进行比较,结果显示扭曲后的标签(warped_label)相较于原标签(src_label)并没有改变。随后我在训练阶段的每一个step中都打印这个扭曲后的标签和原标签进行比较,结果都是不变的。这让我很惊讶,今天,我把学习率调整到了运来的40倍(原来1e-4,现在4e-3),结果才会变。我不知道我遇到了什么问题,所以向作者询问,谢谢您!
'/root/MambaMorph-main/voxelmorph/init.py'代码里面缺少voxelmorph文件夹里面的模块
Traceback (most recent call last):
File "/home/lx/dl/reg/mamba/./scripts/torch/train_cross.py", line 64, in
import generators as src_generators
ModuleNotFoundError: No module named 'generators'
需要在Linux系统里下载好mamba才能把代码跑起来吗
Thank you for your contribution to this work. I have a question: by incorporating the DICE score between labels as part of the loss function, does this imply that the network is a semi-supervised registration network rather than a traditional unsupervised registration network? I would be grateful for your response.
dear authors
It's really a meaningful job. I want to as where can I get the CT-MR registration SR-Reg dataset, the link in your paper seems not accessible.
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