Designed for medical imaging data preprocesing, two types of normalization are implemented:
- Medical imaging mask inerpolation.
- SR image interpolation through Z directions (i.e., thick-slices to thin-slices) with arbitrary user-selected sampling ratios.
from KevinSR import mask_interpolation, SOUP_GAN
for mask interp
new_masks = mask_interpolation(masks, factor)
for SR image interp
thin_slices = SOUP_GAN(thick_slices, factor, prep_type)
#prep_type = 0 or 1 for different preprocessing types (thick-to-thin or thin-to-thin).
1 maintainer
Release files for KevinSR 0.1.20
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| KevinSR-0.1.20.tar.gz | 2.4 MB | Details |
Release files / KevinSR-0.1.20.tar.gz
| Download URL | KevinSR-0.1.20.tar.gz |
|---|---|
| Size | 2.4 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
8efd1b47912c1d5c882767b5d73bc3f2d06d4f1cada021d314e724063a369628
|
|
BLAKE2b-256 checksum How to use checksums |
c2587bc0aeaffa826139c18d81474dc41dc76202be46beb97c6c62559fa4e5bf
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.5
|
