Deep Learning for Chest Radiographs proposes the design of a convolution neural network-based computer-aided diagnostic (CAD) system for diagnosis of pneumonia using chest x-ray images. A total of 200 chest x-ray images (100 normal and 100 pneumonia) are used. The chest radiographs are augmented using geometric transformations such as rotation, translation, and flipping to increase the dataset's size. A total of 12 experiments have been conducted; each of the experiments deals in designing a separate CAD system for the binary classification of chest radiographs. The book contains a comprehensive comparison of various deep feature extraction and classification-based CAD designs for chest radiographs. It also includes an in-depth implementation strategy for data augmentation, data resizing, transfer learning, and deep feature extraction and classification methods for chest radiographs. This book is a valuable resource for academicians, researchers, clinicians, post-graduate/graduate students in Medical Imaging, Computer-Aided Diagnosis, Computer Science and Engineering, Electrical & Electronics Engineering, Biomedical Engineering, Bioinformatics, Bioengineering, and professionals from the IT industry.

Book Information
ISBN 9780323901840
Author Yashvi Chandola
Format Paperback
Page Count 200
Imprint Academic Press Inc
Publisher Elsevier Science & Technology
Weight(grams) 191g