Autopet_Submit
About
Creator:
Contact email:
Version:
4213047d-9e33-498d-b544-127e6003db26
Last updated:
June 23, 2022, 9:52 a.m.
Inputs:
- CT Image (Any CT image)
- PET image (Any PET image)
Outputs:
- Automated PET/CT lesion segmentation (Estimation of a 3D binary lesion segmentation mask based on a two channel input consisting of a PET image volume and the corresponding CT image volume)
Challenge Performance
| Date | Challenge | Phase | Rank |
|---|---|---|---|
| June 23, 2022 | autoPET | Challenge Preliminary Test Set | 138 |
Model Facts
Summary
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Mechanism
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Validation and Performance
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Uses and Directions
This algorithm was developed for research purposes only.
Warnings
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Common Error Messages
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Information on this algorithm has been provided by the Algorithm Editors, following the Model Facts labels guidelines from Sendak, M.P., Gao, M., Brajer, N. et al. Presenting machine learning model information to clinical end users with model facts labels. npj Digit. Med. 3, 41 (2020). 10.1038/s41746-020-0253-3