Suppose we have an array of sample brain scans X of shape (256 × 240 × 240 × 4), and an array Y of target segmentation for tumors, of shape (256 × 240 × 240 × 1), just like in practice session 6.

Scans are in 2D, and we do not care about masks here.

The first dimension corresponds to a patient, the second and third to image rows and columns, and the last dimension to modalities for X or class for Y.

Segmentation is performed by training a pixel classifier.

Among the following approaches to create train and validation sets from an original train set, what is the appropriate one?