I'm planning on training a CNN on CT scans for classification. The problem is CT scans are taken slice by slice, and in a typical scan, there could be more than 200 slices. The number of slices in a scan isn't uniform and depend on the scanning machine and age of the person(for whom the scan is taken).
1)How should I make the number of slices uniform for feeding to a deep learning network?
This sorta problem is handled in NLP by padding a chosen vector( or something similar) to sentences which have lengths less than the predefined length and truncating sentences which have lengths greater than the preset length.
2)Can a similar approach be used to make slices(timesteps) uniform or is there a better way?