nyukat/GLAM
Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis
This tool helps radiologists analyze mammography images for breast cancer diagnosis. It takes high-resolution mammograms (16-bit PNGs) as input and provides predictions for benign or malignant findings, along with visual 'saliency maps' that highlight suspicious regions. Radiologists can use these maps to quickly identify areas of concern and interpret the model's reasoning.
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Use this if you need to quickly identify potential breast lesions in mammography images and understand the specific areas the model is focusing on.
Not ideal if you require real-time, instantaneous analysis, as preprocessing and model inference may take some time depending on your system.
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Last pushed
Aug 18, 2022
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