/Pneumonia_Detection

Pneumonia Detection using Transfer Learning (ResNet50 and VGG-19)

Primary LanguagePythonMIT LicenseMIT

PR's Welcome made-with-python

Pneumonia Detection using Transfer Learning

Approach

Pneumonia detection is commonly predicted using basic CNN models. However , the accuracy of these state of the art models is pretty low. On the other hand, our approach of using Transfer learning, that is, by using VGG-19 and ResNet50, we can get a much better accuracy.

Project

Our project consists of 3 approaches:

  • VGG-19 Model
  • ResNet50 Model
  • ResNet50 Model after Fine-Tuning parameters

Dataset

Dataset consists of images of 2 classes of chest X-ray images:

  1. Diseased
  2. Normal

                   

The dataset can be accessed from the Data Folder.

Model Results

VGG-19

         

ResNet50

         

ResNet50 - Fine Tuned

         

How to Use

  • Clone the repository using :

      $ git clone https://github.com/rishusiva/Pneumonia_Detection
    
  • Enter the directory using:

      $ cd Pneumonia_Detection/
    
  • Install the requirements using:

      $ pip install -r requirements.txt
    
  • Run the demo notebook

Results

  • VGG-19 : 85%
  • ResNet50 : 91%
  • ResNet50 Tuned : 95%

Project Maintainer(s)

Rishikesh S

Your Name Here (Insert Your Image Link In Src

Ananya Negi

Contribution

Contributions are always welcome! You can contribute to this project in the following way:

  • Increasing the accuracy
  • Bug fixes if any
  • Creating an application

Do check out the documentation for Contribution Guidelines.