Hello, I am trying to predict whether a brain tumor has a specific genetic variant (MGMT promoter) from the MRI scans of the brain. I will try to be explicit and give enough context on the problem. There are 585 patients in the training dataset, each containing 4 folders of different MRI modes: T1w, T2w, T1wCE and FLAIR. Inside each of the 4 folders, there are hundreds of dicom files. Also, each patient is assigned a target value of either 0 (brain tumor doesn’t have MGMT promoter) or 1 (there is MGMT promoter in a tumor).
I have written a custom Dataset for data handling but I am not sure what should be the input to a neural network. Specifically, I would like to treat a group of dicoms from a single mode (for example, FLAIR) as a single input, but then the shape of the resulting numpt array is (number_of_dicoms, 224,224) as the images are grayscaled. Is it possible to feed a tensor of such shape to a neural network, or should I feed each dicom separately (e.g. 224x224 tensor)?