Segmentation and analysis of OCT images

This repository is dedicated to the segmentation of optical coherence tomography (OCT) images and the analysis of the plaques that appear on them.

Requirements

• Linux or macOS (Windows has not been officially tested)
• Python 3.8.x

Installation

Step 1: Download and install Miniconda

wget https://repo.anaconda.com/miniconda/Miniconda3-py38_22.11.1-1-Linux-x86_64.sh
chmod +x Miniconda3-latest-Linux-x86_64.sh
./Miniconda3-latest-Linux-x86_64.sh

Step 2: Install FFmpeg and verify that the installation is correct

• Linux

sudo apt update
sudo apt upgrade
sudo apt install ffmpeg -u
ffmpeg -version

• macOS

brew update
brew upgrade
brew install ffmpeg
ffmpeg

Step 3: Clone the repository, create a conda environment, and install the requirements for the repository

git clone https://github.com/ViacheslavDanilov/oct_segmentation.git
cd oct_segmentation
chmod +x create_env.sh
source create_env.sh

Step 4: Initialize git hooks using the pre-commit framework

pre-commit install

Step 5 (optional): Download a raw dataset using DVC

dvc pull dvc/data/raw.dvc

NOTE: Since data storage is organized through Google Drive, you should first request access to the DVC repository.

Data

Source image	Pre-processed image