nyukat/GMIC
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization
This project provides an AI tool to help radiologists and clinicians interpret high-resolution mammography images for breast cancer screening. You input 16-bit PNG mammograms, and the tool outputs predictions for benign and malignant findings, along with visual 'saliency maps' that highlight specific areas in the image contributing to the prediction. This helps medical professionals quickly identify and understand suspicious regions.
183 stars. No commits in the last 6 months.
Use this if you are a radiologist or clinician seeking to augment your breast cancer screening workflow with an interpretable AI system that provides both classification and visual explanations.
Not ideal if you need a solution for medical imaging types other than mammography or if you require real-time processing in a high-throughput clinical environment without robust IT infrastructure.
Stars
183
Forks
52
Language
Jupyter Notebook
License
AGPL-3.0
Category
Last pushed
Jul 25, 2024
Commits (30d)
0
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