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Building an ACL tear detector to spot knee injuries from MRIs with PyTorch (MRNet)
Dear Besbes, Firstly, I thank for your sharing code. It is very nice. I test with sagittal dataset with anterior cruciate ligament tear. However, I could not reproduce your results...
Added latest argparser code and fixed instructions for training.
Hello, thanks for your implementation. However, I found that the "probs" for binary classification doesn't sum up to be 1.0. ``` prediction = model.forward(image.float()) loss = torch.nn.BCEWithLogitsLoss(weight=weight)(prediction, label) loss.backward() optimizer.step()...
![bebesError](https://user-images.githubusercontent.com/46447439/199400890-92ff1222-fee8-40b6-8e68-86850124b73e.PNG) can you please help me solve the error.