Multiple images for one label

Hello I have a dataset that is binary, but each example within the dataset has multiple images. Another way of explaining it is, 1 image but sliced up into multiple images(to get rid of white space). How do I go about putting this into one tensor? Would i just combined them all using numpy? Or are you supposed to use a different dimension, where all 60 images combined would equal 1 label.

To explain this better you would have image 1 that is label 0. This image is split into 60 slices to get rid of white space. How do I make all 60 slices equal the same label, because all 60 of the slices might not contain what i’m looking for.

I don’t completely understand the use case and what “white spaces” refers to in your example.
How did you split the image into 60 slices and what does each slice represent?

This is the dataset and this is how they are sliced. Quick Blood Clot Slicing | Kaggle