I am working with Medical Images, where I have 130 Patient Volumes, each volume consists of  N  number of DICOM Images/slices.
The problem is that between the volumes the the number of slices  N , varies.
Majority, 50% of volumes have 20 Slices, rest varies by 3 or 4 slices, some even more than 10 slices (so much so that interpolation to make number of slices equal between volumes is not possible)
I am able to use Conv3d for volumes where the depth  N  (number of slices) is same between volumes, but I have to make use of entire data set for the classification task. So how do I incorporate entire dataset and feed it to my network model ?