Knee-Osteoarthritis-Prediction

Knee Osteoarthritis Prediction

🎯 Goal

The objective of this project is to classify xrays of Knee Xrays into 5 distinct categories based on severity of the disease.

🧵 Dataset

The link for the dataset used in this project: https://www.kaggle.com/datasets/shashwatwork/knee-osteoarthritis-dataset-with-severity/data

The dataset consists of four subdirectories: train, test, auto test and val (test and auto_test are the same). All four contain 5 subdirectories, each representing a severity of osteoarthritis. The test and auto_test subdirectory contains 1346 images in total, while the train subdirectory contains 5778 images in total and the val subdirectory contains 826 images in total.

🧾 Description

The project deals with multi-class classification, classifying images into 5 grades of severity.

🧮 What I had done!

To achieve our goals, the following steps were implemented:

• Images were loaded using keras.utils and normalized to the range 0 to 1.

• Images were resized to a fixed size of 128x128 pixels.

• Custom and pre-trained models were used for this task.

📚 Libraries Needed

• Keras

• Tensorflow

• Numpy

• Matplotlib

Loss and Accuracy

||Accuracy||94.15%|| ||Loss||15.68%||