Super-resolution interpolation tool for medical images.
This inference code supports:
- Thick-slices to thin-slices SR interpolation with arbitrarily user-selected sampling ratios (e.g., from 2x to 6x).
- Medical imaging mask inerpolation.
SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks. Tomography 2022, 8(2), 905-919
Kuan Zhang, Haoji Hu, Kenneth Philbrick, Gian Marco Conte, Joseph D. Sobek, Pouria Rouzrokh, Bradley J. Erickson
Install the package KevinSR.
from KevinSR import mask_interpolation, SOUP_GAN
# for SR image interp (prep_type=0: thick-to-thin; 1: thin-to-thin)
thin_slices = SOUP_GAN(thick_slices, factor, prep_type)
# for mask interp
new_masks = mask_interpolation(masks, factor)
Example_0 (thick_to_thin):
Example_1 (sparse_to_thin):
Mask_interpolation: