MungoMeng/Survival-AdaMSS
AdaMSS: Adaptive Multi-Modality Segmentation-to-Survival Learning for Survival Outcome Prediction
This project helps medical professionals predict patient survival outcomes from medical images. It takes PET and CT scans as input and identifies tumor regions, then expands its focus to other relevant areas to provide a survival prediction. Oncologists, radiologists, and other clinicians involved in cancer treatment and prognosis would use this.
No commits in the last 6 months.
Use this if you need to predict patient survival from PET/CT images, aiming for more accurate and comprehensive insights than traditional methods.
Not ideal if you are working with other types of medical images (e.g., MRI only) or predicting non-survival related outcomes.
Stars
16
Forks
1
Language
Python
License
GPL-3.0
Category
Last pushed
Jan 01, 2025
Commits (30d)
0
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