nyukat/3D_GMIC
3D-GMIC: an efficient deep neural network to find small objects in large 3D images
This project helps radiologists analyze 3D digital breast tomosynthesis images to find small lesions that could indicate breast cancer. It takes a pre-processed breast tomosynthesis image and outputs the probability of benign or malignant findings for the image, along with visual maps showing areas of concern. Radiologists and breast imaging specialists would use this to assist in cancer detection and interpretation.
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Use this if you need an efficient way to automatically identify potential breast cancer lesions and visualize suspicious areas within large 3D breast tomosynthesis scans.
Not ideal if you need to process different types of medical images beyond breast tomosynthesis or require a system that is trained with precise, pixel-level lesion annotations.
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31
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Language
Python
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Last pushed
Oct 18, 2022
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