AutoProSeq - automatic classification of sequence types for prostate mpMRI
XGBoost-based automatic classification of sequence types for prostate mpMRI into T2W, DWI, ADC, DCE and others (any other sequence type) using metadata alone. Works as a CLI, allows direct application to DICOM datasets or CSV/tsv/Excel/parquet datasets, features integration for Orthanc and DICOM-web as RESTful APIs. This was applied to all data on ProCAncer-I to derive initial results for sequence types. Refines predictions using rule-based heuristics for T2W, DWI and ADC.
Topics
Collections
Details
- License:
- MIT
- Maturity:
- Emerging
- Cost:
- Free of charge (with restrictions)
- Tool Type:
- api, command-line tool
- Operating Systems:
- Linux
- Programming Languages:
- Python
- Added:
- 12/2/2025
- Last Updated:
- 12/3/2025
Operations
Data Inputs & Outputs
Image annotation
Inputs
Publications
Documentation
Other
https://github.com/CCIG-Champalimaud/metadata-classificationRepository containing the code, README and additional information on how to run the tool. If used as an API (when integrated with Orthanc or DICOM-web), the documentation is available upon launching the API at <api-url>/docs.
Links
Repository
https://github.com/CCIG-Champalimaud/metadata-classification(Repository containing code, README and additional usage information for this tool.)