Deep Learning For Chest Radiographs by Yashvi Chandola, Paperback | Indigo Chapters

Deep Learning for Chest Radiographsproposes 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. Provides insights into the theory, algorithms, implementation and application of deep learning techniques for medical images such as transfer learning using pre-trained convolution neural networks, series networks, DAG networks, light-weight CNN models, deep feature extraction and Conventional machine learning approaches for feature selection, feature dimensionality reduction and classification using support vector machine, neuro-fuzzy classifiers. Covers the various augmentation techniques that can be used with medical images and the CNN based CAC system designs for binary classification of medical images focusing on chest radiographs. Investigates the development of optimal CAC system design with deep feature extraction and classification of chest radiographs by comparing the performance of 12 different CAC system designs. | Deep Learning For Chest Radiographs by Yashvi Chandola, Paperback | Indigo Chapters