Why you get a common foreground mask in advance in preprocessing? about 3dunetcnn HOT 7 CLOSED

Hi @namco1992! Good question. My goal was to keep the spacing of the images identical to each other. So I cropped all of the images down to the smallest size that included all the foreground pixels from all of the images. I then resized the images identically so that they would all be the same size with the same image spacing.

Honestly, I don't know if this is beneficial. If a model is trained with a large amount of data and with sufficient data augmentation, the image spacing might not make even a small difference. An alternative would be to crop each image individually and then resize to the input size for the model. This results in differing image spacing between the input images.

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Hi @ellisdg ,
Thanks for your response, I didn't consider about the spacing before, but I think it's better to keep the identical spacing.

I have another question, I noticed that you only choose T1, T1c and flair as training modalities, is it only because you would like to save some memory space?

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Actually, I use T1, T1c and flair because those are the modalities present in a private dataset in which I am trying to detect brain tumors.

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HI @ellisdg
Did you classify all the sub tumor classes(edema,necrotic,enh,non-enh) or you classified tumor as a whole??

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So far, I have only done tumor as a whole. The sub classes are not important to me at this time.

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@ellisdg
Ok.. thank you for making ur code online... there is a lot of information to learn from it.. I really learnt something by working on your code..

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Hi @ellisdg ,
Thank you, I also get so much help here just like @poornasandur . All the best.

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