aishstha/Segment-and-quantify-cells

This initiative supports researchers in automating nuclei segmentation through a deep learning model trained on our dataset, providing quantified results in an Excel file. It facilitates the identification and quantification of cell nuclei.

Prerequisites

• Python - v3.10.8
• cv2 - 4.6.0
• matplotlib - 3.6.2
• pandas - 1.5.2
• skimage - 0.19.3

The repository's scripts are organized into three sections: pre-processing, deep learning model, and post-processing

Setup

Clone the repository, install the dependencies and get started right away.

$ git clone git@github.com:aishstha/Segment-and-quantify-cells.git](https://github.com/aishstha/Segment-and-quantify-cells.git)
$ cd Segment-and-quantify-cells

For post-processing

Example :

$ ./segment_script.py  "Data/IXMtest_C05_s7_w1F71963FB-8F29-41CB-A5F5-07CB9584BBC5.tif"

Usage

You can manually Install packages mentioned above (cv2, numpy, matplotlib, pandas, sys, skimage).

OR

Use the conda environment file of this project. For more information, check environment.yml

Conda Environment

Use the terminal or an Anaconda Prompt for the following steps:

1. Create the environment from the environment.yml file:

$ conda env create -f environment.yml

2. Activate the new environment: conda activate segmentation

3. Verify that the new environment was installed correctly:

$ conda env list