Deep Learning for Chest Radiographs

Computer-Aided Classification

Yashvi Chandola, Jitendra Virmani, H.S Bhadauria, Papendra Kumar
Elsevier S&T
228 pages
ISBN: 978-0323901840
August 2021

Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." In the CAC system designs implemented in this book, a total of 200 chest radiograph images consisting of 100 Normal images and 100 Pneumonia images have been used. These chest radiographs are augmented using geometric transformations, such as rotation, translation, and flipping, to increase the size of the dataset for efficient training of the Convolutional Neural Networks (CNNs).