https://github.com/emreozogul/dva
Dynamic viability analysis of cancer cells via OpenCV
https://github.com/emreozogul/dva
eel html-css-javascript opencv python
Last synced: about 2 months ago
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Dynamic viability analysis of cancer cells via OpenCV
- Host: GitHub
- URL: https://github.com/emreozogul/dva
- Owner: emreozogul
- License: mit
- Created: 2024-03-07T14:22:22.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-12T00:38:41.000Z (about 2 years ago)
- Last Synced: 2025-04-04T06:41:43.188Z (about 1 year ago)
- Topics: eel, html-css-javascript, opencv, python
- Language: JavaScript
- Homepage:
- Size: 66.1 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Dynamic Viability Analysis of Drug-Treated Cancer Cells with Incremental Learning Algorithms (DVA)
## Introduction
This project, DVA, develops a desktop application to classify drug-treated cancer cells using machine learning. It aims to automate the analysis of cell viability and death levels, enhancing the accuracy and speed of research in cancer treatments.
## Features
- **Automated Analysis**: Automatically determine the viability of cancer cells from images.
- **Advanced Image Processing**: Includes Threshold algorithms, Contour Detection etc. to prepare images for machine learning analysis.
- **Incremental Machine Learning Model**: Uses an Incremental Machine learning model that adapts and improves over time.
- **User-Friendly Interface**: Designed to be accessible for both technical and non-technical users.
## Installation
Clone the repository:
```bash
git clone https://github.com/emreozogul/DVA.git
cd DVA
pip install -r requirements.txt
```
Install the required packages:
```bash
pip install -r requirements.txt
```
or :
```bash
pip install eel opencv-python scikit-learn wxPython pandas numpy
```
Run the application with:
```python
python app.py
```
## Libraries
### Python
Eel - https://github.com/python-eel/Eel
OpenCV, Sklearn, Wx, Pandas, NumPy
### JS Scripts
Tiff.js - https://github.com/seikichi/tiff.js
Canvastotiff.js - https://github.com/motiz88/canvas-to-tiff
Cropper.js - https://github.com/fengyuanchen/cropperjs
JQuery
## Authors and Acknowledgement
- Emre Evcin
- Emre Özoğul
- Mehmet Eren Sönmez
Special thanks to our supervisors, Assoc. Prof. Dr. Kaya Oğuz and Prof. Dr. Zeynep Fırtına Karagonlar.
The project has earned the right to receive support from The Scientific and Technological Research Council of Turkey (TÜBİTAK).
Project Link: [https://github.com/emreozogul/DVA](https://github.com/emreozogul/DVA)