HiLab-git / SSL4MIS

Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

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train own 2D pictures

cebain opened this issue · comments

commented

hello,thanks for your revision very much。 I still want to ask a question。 We can see that the h5 file includes both image and label data, and when we train,for unlabeld data, we just extract volume batch which is the image data。 However, if I don't have labels of all data,I just have labels for some of the data, which really needs smei-supervise, then how should I write
the h5 file, or I just read image for 2D pictures?

commented

Have you found a solution?

Hello, my dataset is a 2D image, have you solved this problem, can we talk?