ViacheslavDanilov/oct_segmentation
This repository is dedicated to the segmentation of optical coherence tomography (OCT) images and the analysis of the plaques that appear on them
This project helps cardiovascular specialists accurately identify and quantify atherosclerotic plaque features from Optical Coherence Tomography (OCT) images. You input raw OCT images, and it outputs segmented images highlighting the lumen, fibrous cap, lipid core, and vasa vasorum. This tool is for cardiologists, researchers, and medical imaging specialists working on diagnostics and therapeutic interventions for cardiovascular diseases.
Use this if you need precise, automated segmentation of atherosclerotic plaque features in OCT images to aid in cardiovascular diagnostics and research.
Not ideal if you are working with other medical imaging modalities or require analysis of cardiovascular structures other than atherosclerotic plaques in OCT.
Stars
10
Forks
1
Language
Python
License
MIT
Category
Last pushed
Jan 01, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ViacheslavDanilov/oct_segmentation"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
dipy/dipy
DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for...
Project-MONAI/MONAI
AI Toolkit for Healthcare Imaging
Project-MONAI/MONAILabel
MONAI Label is an intelligent open source image labeling and learning tool.
neuronets/nobrainer
A framework for developing neural network models for 3D image processing.
Project-MONAI/monai-deploy-app-sdk
MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify...