README.md

Pneumonia-Detection-DeepLearning-CNN

Detecting Pneumonia in Chest X-ray Images using Convolutional Neural Network

Abstract

Pneumonia is an infection that inflames the air sacs in one or both lungs. The air sacs may fill with fluid or pus (purulent material), causing cough with phlegm or pus, fever, chills, and difficulty breathing. A variety of organisms, including bacteria, viruses and fungi, can cause pneumonia.

Dataset

Dataset Name     : Chest X-Ray Images (Pneumonia)
Dataset Link     : Chest X-Ray Images (Pneumonia) Dataset (Kaggle)
                 : Chest X-Ray Images (Pneumonia) Dataset (Original Dataset)
Original Paper   : Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning
                   (Daniel S. Kermany, Michael Goldbaum, Wenjia Cai, M. Anthony Lewis, Huimin Xia, Kang Zhang)
                   https://www.cell.com/cell/fulltext/S0092-8674(18)30154-5

Dataset Details
Dataset Name            : Chest X-Ray Images (Pneumonia)
Number of Class         : 2
Number/Size of Images   : Total      : 5856 (1.15 Gigabyte (GB))
                          Training   : 5216 (1.07 Gigabyte (GB))
                          Validation : 320  (42.8 Megabyte (MB))
                          Testing    : 320  (35.4 Megabyte (MB))

Model Parameters
Machine Learning Library: Keras
Base Model              : Custom Deep Convolutional Neural Network
Optimizers              : Adam
Loss Function           : binary_crossentropy

For Custom Deep Convolutional Neural Network : 
Training Parameters
Batch Size              : 64
Number of Epochs        : 30
Training Time           : 2 Hours

Output (Prediction/ Recognition / Classification Metrics)
Testing
Precision               : 87.64%
Recall                  : 98.21%
F1-Score                : 92.62%

Sample Input:

Results:

Sample Output:

Confusion Matrix:

Tools / Libraries

Language                : Python3
Tools/IDE               : Anaconda
Libraries               : Keras, TensorFlow