MrGiovanni / MrGiovanni/ModelsGenesis
Reproduction of BraTs results
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Description
Hi !
First, thank you for making your incredible work available. Your results are outstanding and the code is pretty easy to understand.
In order to use your work in another application that I am investigating I wanted first to replicate your results on the BraTs dataset.
I have downloaded and preprocessed the data : resizing the images to 64x64x64 and normalizing between 0 and 1.
However, when finetuning Genesis CT I don't manage to get anything close to your results.
Is there something I am missing ? The whole image has to be fed to the network or split in patches ? Also in the code example given in the keras folder num_classes is set to 2 for segmentation which I am not sure to understand as the convolution will create (2, 64, 64, 64) sized mask.
Thank you for your help,
Regards,
Camille
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the Keras folder and its fine-tuning example, then compare the issue's BraTS preprocessing with the repository's expected input setup. Investigate the whole-volume versus patch question and the meaning of num_classes=2; done means the intended configuration and output shape are clear enough to reproduce the reported results.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- keras
- Domain
- computer-vision, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100