Knee Osteoarthritis Detection and Severity Prediction (Using Machine Learning)

Authors:

Anjali Gaur

Shaina Mehta

Submitted To:

Prof. (Dr.) M. Partha Sarathi

Guided By:

Prof. (Dr.) M. Partha Sarathi

Acknowledgement:

Unsung Heros of Stack Overflow, Github, NPTEL Course, Wikipedia, Edureka, Coursera, Kaggle, Towards Data Science and other Web Blogs and Youtube Videos.

The Project Supervisor and My Project Partner (Anjali Gaur).

My Parents and My Grandmother

My friends and juniors - Leah Khan, Rahul Sawhney, Nikhil J. Dutta, Rakshit Walia, Aadil Sehrawat, Venkatesh, Arushi Kumar, Ayushi Pandit, Deepansha Adlakha, Amartya Sumukh Varma, Vanshika Gupta, Harjot Kaur, Prerna Singh, Tanya Yadav.

About The Project:

This project has the following objectives:

1. To make a Deep Learning model that will identify and assess the severity of knee osteoarthritis using Residual Networks.

2. Developing a website in HTML, Bootstrap CSS, JavaScript, and Python will serve as a demonstration of the achieved outcome.

Link of the Dataset:

https://drive.google.com/drive/folders/12q0klcozfD8y6Vj8BhNwBBpHb6lrJNSZ?usp=sharing

Link of the Code of Image Processing and Machine Learning Pipeline:

https://github.com/shaina-12/KneeNet.git

Link of Research Paper:

https://ieeexplore.ieee.org/abstract/document/10306649

Correction Needed in the Paper = Instead of 7096 images, 7060 images are used for training, validation and testing.

Refereces and Bibliography: