andreped/DMDetect
Code relevant for training, evaluating, assessing, and deploying CNNs for image classification and segmentation of Digital Mammography images
This project helps radiologists and medical researchers analyze digital mammography images. It takes raw or preprocessed mammograms as input and provides classifications of whether cancer is present, or detailed segmentations outlining areas like cancer, mammary glands, pectoral muscles, and nipples. This tool is for professionals who interpret mammograms and need assistance with automated detection and precise region identification.
No commits in the last 6 months.
Use this if you need to automatically classify digital mammograms for the presence of breast cancer or to segment specific anatomical regions within the images.
Not ideal if you are looking for a complete, production-ready clinical diagnostic tool without further development and validation.
Stars
9
Forks
1
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Mar 31, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/andreped/DMDetect"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
nyukat/breast_cancer_classifier
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
lishen/end2end-all-conv
Deep Learning to Improve Breast Cancer Detection on Screening Mammography
naomifridman/BreastDCEDL
BreastDCEDL is a deep learning–ready DCE-MRI dataset of 2,070 breast cancer patients, sourced...
nyukat/GMIC
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly...
cbailes/awesome-ai-cancer
Awesome artificial intelligence in cancer diagnostics and oncology