Mr-TalhaIlyas/TSFD
Nuclei segmentation and classification (Cancer cells)
This project helps pathologists and medical researchers automatically analyze microscope images of tissue biopsies. It takes standard hematoxylin and eosin-stained histology images as input and identifies individual cell nuclei, classifying them by type and flagging potential cancer cells. It's designed for professionals involved in cancer diagnostics or pathology research.
No commits in the last 6 months.
Use this if you need to precisely segment and classify cell nuclei in H&E stained histopathology images to support cancer diagnosis or research.
Not ideal if you are working with non-histology images or require analysis of cellular structures other than nuclei.
Stars
25
Forks
5
Language
Jupyter Notebook
License
—
Category
Last pushed
Jun 04, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Mr-TalhaIlyas/TSFD"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
nilearn/nilearn
Machine learning for NeuroImaging in Python
aramis-lab/clinica
Software platform for clinical neuroimaging studies
TissueImageAnalytics/tiatoolbox
Computational Pathology Toolbox developed by TIA Centre, University of Warwick.
nipreps/mriqc
Automated Quality Control and visual reports for Quality Assessment of structural (T1w, T2w) and...
nadeemlab/DeepLIIF
Deep Learning Inferred Multiplex ImmunoFluorescence for IHC Image Quantification...