Hello @DL_Begin,
Yes, this is easily done, though not sure exactly about your goal, the exact code/approach depends on that. The most trivial solution below:
import SimpleITK as sitk
import numpy as np
# Create random image, note that numpy (z,y,x) and ITK/SimpleITK (x,y,z) index order are reveresed
arr = np.random.random([284,143,143])
original_volume = sitk.GetImageFromArray(arr)
# Resample to the new desired size
new_size = [128, 128, original_volume.GetSize()[-1]]
resampled_volume = sitk.Resample(original_volume,new_size)
#Extract the slices into a list
slice_list = [resampled_volume[:,:,i] for i in range(resampled_volume.GetSize()[-1])]
If you want to perform some operation on a slice by slice fashion and then resample the volume to a new size I recommend using the Pythonic slicing_decorator solution provided by @blowekamp and then resampling as above.