lyhkevin/Graph-V-Net
A Hierarchical Graph V-Net with Semi-supervised Pre-training for Breast Cancer Histology Image Classification" (IEEE TMI)
This tool helps pathologists and medical researchers quickly and accurately classify breast cancer in whole slide images. It takes raw whole slide images of breast tissue biopsies as input. The output is a detailed classification for each patch within the image, categorizing it as normal, benign, carcinoma in situ, or invasive carcinoma, aiding in diagnosis and research.
No commits in the last 6 months.
Use this if you need an automated system to assist with the diagnosis and classification of breast cancer directly from high-resolution histological whole slide images.
Not ideal if you are working with microscopic images that are not whole slide images or if you need to classify other types of cancer.
Stars
24
Forks
3
Language
Python
License
—
Category
Last pushed
Oct 23, 2023
Commits (30d)
0
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