AICAN-Research/FAST-Pathology
⚡ Open-source software for deep learning-based digital pathology
This software helps pathologists and medical researchers analyze whole slide images (WSIs) with deep learning. It takes digital pathology slides as input and uses AI models to identify and highlight specific features like cancerous regions or cell types. Pathologists and researchers can use this tool to automate and enhance their diagnostic and research workflows.
141 stars. No commits in the last 6 months.
Use this if you need to apply deep learning models to digital pathology slides for tasks like segmentation, classification, or object detection, without needing to write code.
Not ideal if you are looking for a general-purpose image analysis tool not specifically designed for whole slide images in pathology.
Stars
141
Forks
26
Language
C++
License
BSD-2-Clause
Category
Last pushed
Jun 14, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/AICAN-Research/FAST-Pathology"
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...