normaltwinpet
Generate a whole-body normal twin PET from a CT image, using the CT-only model from:
Hinge et al., Normal twin PET: personalized generative modeling for confounder correction and anomaly detection in whole-body PET/CT, Scientific Reports 15, 42662 (2025). https://doi.org/10.1038/s41598-025-26827-y
Input is a CT, output is the normal twin PET, on the same voxel grid as the CT.
The output is normalized as image-derived lean-body-mass SUV (see ID-uptake-values).
Usage
pip install normaltwinpet
normaltwinpet -i ct.nii.gz -o ntpet.nii.gz
Uses CUDA if available, otherwise CPU (slow). Override with --device.
On first run the weights (~250 MB) are downloaded from the GitHub release and
cached in the user cache directory (~/.cache/normaltwinpet on Linux). Set
NORMALTWINPET_HOME to use another location.
Notes
The CT is resampled to 2 mm and cropped/padded to 256x256 in-plane for the network, then resampled back to the input grid. Anatomy outside the central 256x256 (512 mm) in-plane field of view is not predicted and will be zero.
1 maintainer
Metadata
1 maintainer
Release files for normaltwinpet 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| normaltwinpet-0.3.0.tar.gz | 6.7 kB | Without provenance | Details for normaltwinpet-0.3.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| normaltwinpet-0.3.0-py3-none-any.whl | Python 3 | none | any | Details for normaltwinpet-0.3.0-py3-none-any.whl |
Total release size: 16.0 kB
Release files / normaltwinpet-0.3.0.tar.gz
| Download URL | normaltwinpet-0.3.0.tar.gz |
|---|---|
| Size | 6.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
cd928507ddceab14c7b934ecf3c5f0ae3e8aadedee74641abbf4ea171e5eb67b
|
|
BLAKE2b-256 checksum How to use checksums |
99ad94c0dbdd28ed1670791f18cb819bc2a8c10b8ecfcf6930d9fba25fe1ae9f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
uv/0.13.6 {"installer":{"name":"uv","version":"0.13.6","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|
Release files / normaltwinpet-0.3.0-py3-none-any.whl
| Download URL | normaltwinpet-0.3.0-py3-none-any.whl |
|---|---|
| Size | 9.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
de75767dfa92ef0fed39d2099f154d558ac83d84d7bb08d3f0eaa778b1230280
|
|
BLAKE2b-256 checksum How to use checksums |
69be24f9dceb2a015ea1cd6b249a0f25c166ce93e8edbc53051c24388906bb85
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
uv/0.13.6 {"installer":{"name":"uv","version":"0.13.6","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
|
Security for normaltwinpet 0.3.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
