Quantitative Analysis of Chromatin Organization

This repository contains the Python code for the quantitative analysis of chromatin organization in cell nuclei of small-cell and large-cell neuroendocrine lung cancer. We utilize the PyRadiomics package and the StarDist model for segmentation of cell nuclei.

Project Description

This project aims to provide tools for automated quantitative analysis to assist in the differentiation and study of small-cell and large-cell neuroendocrine lung cancers based on their chromatin organization. Using advanced image analysis techniques and machine learning models, we extract valuable radiomic features that can be used in cancer research and diagnosis.

Features

• Cell Nuclei Segmentation: Utilizes the StarDist model for accurate segmentation of cell nuclei from microscopic images.
• Feature Extraction: Employs the PyRadiomics package to extract a wide range of radiomic features from the segmented nuclei.
• Analysis Pipeline: Offers a streamlined workflow for processing images, extracting features, and preparing the data for further statistical analysis.

Data Structure

Ensure your Google Drive contains the data organized as follows:

MyDrive/
└── Colab Notebooks/
    └── MIA/
        └── Project_4/
            ├── LCNEC/
            │   ├── Folder1/
            │   │   ├── HE/
            │   │   └── CancerMask/
            │   ├── Folder2/
            │   │   ├── HE/
            │   │   └── CancerMask/
            │   └── ...
            └── SCLC/
                ├── Folder1/
                ├── Folder2/
                └── ...