{"product_id":"deep-learning-for-chest-radiographs-yashvi-chandola-9780323901840","title":"Deep Learning for Chest Radiographs: Computer-Aided Classification","description":"\u003cp\u003e\u003ci\u003eDeep Learning for Chest Radiographs\u003c\/i\u003e 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.\" Pneumonia is an infectious disease mostly caused by a bacteria or a virus. The prime targets of this infectious disease are children below the age of 5 and adults above the age of 65, mostly due to their poor immunity and lower rates of recovery. Globally, pneumonia has prevalent footprints and kills more children as compared to any other immunity-based disease, causing up to 15% of child deaths per year, especially in developing countries. Out of all the available imaging modalities, such as computed tomography, radiography or X-ray, magnetic resonance imaging, ultrasound, and so on, chest radiographs are most widely used for differential diagnosis between 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). A total of 12 experiments were conducted for the binary classification of chest radiographs into Normal and Pneumonia. It also includes in-depth implementation strategies of exhaustive experimentation carried out using transfer learning-based approaches with decision fusion, deep feature extraction, feature selection, feature dimensionality reduction, and machine learning-based classifiers for implementation of end-to-end CNN-based CAC system designs, lightweight CNN-based CAC system designs, and hybrid CAC system designs for chest radiographs.\u003c\/p\u003e \u003cp\u003eThis book is a valuable resource for academicians, researchers, clinicians, postgraduate and graduate students in medical imaging, CAC, computer-aided diagnosis, computer science and engineering, electrical and electronics engineering, biomedical engineering, bioinformatics, bioengineering, and professionals from the IT industry.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Yashvi Chandola, Jitendra Virmani, H. S. Bhadauria\u003cbr\u003e\u003cb\u003eISBN-10:\u003c\/b\u003e 0323901840\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9780323901840\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Academic Press\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 07\/22\/2021\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 228\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.88lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.25h x 7.50w x 0.48d","brand":"Yashvi Chandola","offers":[{"title":"Paperback","offer_id":44522642079999,"sku":"9780323901840","price":100.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_7cfe43f9-a06b-4849-8d45-a484adc54631.jpg?v=1700158317","url":"https:\/\/www.whiterainbookhouse.com\/products\/deep-learning-for-chest-radiographs-yashvi-chandola-9780323901840","provider":"WR Book House","version":"1.0","type":"link"}