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." 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.

This 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.

Provides insights into the theory, algorithms, implementation, and application of deep-learning techniques for medical images such as transfer learning using pretrained CNNs, series networks, directed acyclic graph networks, lightweight 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 an optimal CAC system design with deep feature extraction and classification of chest radiographs by comparing the performance of 12 different CAC system designs

Acerca de los autores

Yashvi Chandola received her B-Tech (Hons.) in Computer Science and Engineering from Women Institute of Technology, Dehradun, Uttarakhand in 2018. She has completed her M-Tech (Hons.) in Computer Science and Engineering from Govind Ballabh Pant Institute of Engineering and Technology, Pauri Garhwal, Uttarakhand in 2020. Her research interests include application of machine learning and deep learning algorithms for analysis of medical images.

Jitendra Virmani received his B-Tech (Hons.) in Instrumentation Engineering from Sant Longowal Institute of Engineering and Technology, Punjab in 1999 and M-Tech in Electrical Engineering with specialization in Measurement and Instrumentation from the Indian Institute of Technology, Roorkee in 2006. He served in the academia for nine years before joining the PhD programme in 2009 at Biomedical Instrumentation Laboratory, Electrical Engineering Department, Indian Institute of Technology, Roorkee as a full time Research Scholar under MHRD Assistantship. He received his PhD from the Indian Institute of Technology, Roorkee in 2013. After his PhD he served in Academia for Jaypee University of Information Technology, Solan, Himachal Pradesh and Thapar Institute of Engineering and Technology, Patiala, Punjab before joining CSIR-CSIO, Chandigarh in August 2016. He is presently working at CSIR-CSIO, Chandigarh. He is a Life member of the Institute of Engineers (IEI), India and Computer Society of India. He has published 85 papers in various journals, conferences and Book chapters with various reputed publishers. He has delivered more than 35 expert talks on various platforms basically on application of machine learning and deep learning algorithms for medical images. He is Editorial Board Member of International Journal of Image Mining published by Inderscience Publishers. His research interests include application of machine learning and deep learning algorithms for analysis of medical images.

H.S Bhadauria received his B-Tech in Computer Science and Engineering from Aligarh Muslim University, Aligarh in 1999, and M-Tech in Electronics Engineering from Aligarh Muslim University, Aligarh in 2004. He received his PhD on Detection and Segmentation of Brain Hemorrhage using CT images from Biomedical Signal and Image Processing Laboratory, Indian Institute of Technology - Roorkee in 2013. During his PhD he worked on enhancing the detection and segmentation of brain hemorrhage using CT imaging modality. He has served in academia for more than 12 years. He is presently serving as a Professor in the Department of Computer Science & Engineering at Govind Ballabh Pant Institute of Engineering and Technology, Pauri Garhwal, Uttarakhand. He is a life member of Institute of Engineers (IEI), India. He has published more than 60 research papers in International and National Journals and Conferences. His areas of research interest are Digital Image and Digital Signal Processing.

Papendra Kumar received his B.E in Computer Science and Engineering from Govind Ballabh Pant Institute of Engineering and Technology, Pauri Garhwal, Uttarakhand in 2007 and M-Tech in Digital Signal Processing from Govind Ballabh Pant Institute of Engineering and Technology, Pauri Garhwal, Uttarakhand in 2011. He is presently serving as an Assistant Professor in the Department of Computer Science & Engineering at Govind Ballabh Pant Institute of Engineering and Technology, Pauri Garhwal, Uttarakhand. His areas of research interest are Digital Image and Digital Signal Processing.

"Sobre este t�tulo" puede pertenecer a otra edici�n de este libro.

Descripci�n de la librer�a

The Saint Bookstore has a range of over 1 million titles available.

Ver la p�gina web de la librer�a

Informaci�n empresarial del vendedor

SB ONLINE LTD
50 Devonshire Road, Southport, PR9 7BZ, United Kingdom

Condiciones de venta y env�o

Condiciones de venta

Please order through the Abebooks checkout. We only take orders through Abebooks - We don't take direct orders by email or phone.

Refunds or Returns: A full refund of the purchase price will be given if returned within 30 days in undamaged condition.

As a seller on abebooks we adhere to the terms explained at http://www.abebooks.co.uk/docs/HelpCentral/buyerIndex.shtml - if you require further assistance please email us at orders@thesaintbookstore.co.uk

Derecho a cancelaci�n

Si eres un consumidor puedes cancelar el presente contrato de acuerdo con lo indicado a continuaci�n. Son consumidores las personas f�sicas que act�en con un prop�sito ajeno a su actividad comercial, empresarial, oficio o profesi�n.

Documento de informaci�n al consumidor y usuario sobre el desistimiento

Derecho de desistimiento:

Tienes derecho a desistir del presente contrato en un plazo de 14 d�as naturales sin necesidad de justificaci�n.

El plazo de desistimiento expirar� a los 14 d�as naturales del d�a en que t� o un tercero que hayas indicado, distinto del transportista, adquiera la posesi�n material del �ltimo bien, componente o pieza.

Para ejercer el derecho de desistimiento, deber�s notificarnos a THE SAINT BOOKSTORE, 50 Devonshire Road, PR9 7BZ, Southport, United Kingdom, 44 17042241479, de tu decisi�n de desistir del contrato a trav�s de una declaraci�n inequ�voca (por ejemplo, una carta enviada por correo postal, fax o correo electr�nico). Podr�s utilizar el modelo de formulario de desistimiento que figura a continuaci�n, aunque su uso no es obligatorio. Tienes asimismo la opci�n de cumplimentar y enviar electr�nicamente el modelo de formulario de desistimiento o cualquier otra declaraci�n inequ�voca a trav�s de nuestro sitio web a "Mis pedidos" en "Mi cuenta". Si recurres a esta opci�n, te comunicaremos sin demora en un soporte duradero (por ejemplo, por correo electr�nico) la recepci�n de dicho desistimiento.

Para cumplir el plazo de desistimiento, basta con que la comunicaci�n relativa al ejercicio por tu parte de este derecho sea enviada antes de que venza el plazo correspondiente.

Consecuencias del desistimiento:

En caso de desistimiento por tu parte, te devolveremos todos los pagos recibidos de ti, incluidos los gastos de entrega (con la excepci�n de los gastos adicionales resultantes de la elecci�n por tu parte de una modalidad de entrega diferente a la modalidad menos costosa de entrega ordinaria que ofrezcamos) sin ninguna demora indebida y, en todo caso, a m�s tardar 14 d�as naturales a partir de la fecha en la que se nos informes de tu decisi�n de desistir del presente contrato. Procederemos a efectuar dicho reembolso utilizando el mismo medio de pago empleado por ti para la transacci�n inicial, a no ser que hayas dispuesto expresamente lo contrario; en todo caso, no incurrir�s en ning�n gasto como consecuencia del reembolso.

Podremos retenerte el reembolso hasta haber recibido los bienes, o hasta que hayas presentado una prueba de la devoluci�n de los mismos, seg�n qu� condici�n se cumpla primero. Deber�s devolvernos o entregarnos directamente los bienes a THE SAINT BOOKSTORE, 50 Devonshire Road, PR9 7BZ, Southport, United Kingdom, 44 17042241479, sin ninguna demora indebida y, en cualquier caso, a m�s tardar en el plazo de 14 d�as naturales a partir de la fecha en que nos comuniques tu decisi�n de desistimiento del contrato. Se considerar� cumplido el plazo si efect�as la devoluci�n de los bienes antes de que haya concluido dicho plazo. Deber�s asumir el coste directo de devoluci�n de los bienes. Solo ser�s responsable de la disminuci�n de valor de los bienes resultante de una manipulaci�n distinta a la necesaria para establecer la naturaleza, las caracter�sticas y el funcionamiento de los bienes.

Excepciones al derecho de desistimiento:

La entrega de peri�dicos, publicaciones especializadas o revistas con la excepci�n de contratos de suscripci�n; y
La entrega de contenido digital (incluyendo apps, software digital e-books, MP3, etc.) que no hubiera sido entregado en un medio tangible (por ejemplo: CD o DVD), si al realizar tu pedido has aceptado que podemos proceder al env�o del producto y que no resulta posible su cancelaci�n una vez comienza la entrega.

Modelo de formulario de desistimiento

(S�lo debe cumplimentar y enviar el presente formulario si desea desistir del contrato)

A la atenci�n de: (THE SAINT BOOKSTORE, 50 Devonshire Road, PR9 7BZ, Southport, United Kingdom, 44 17042241479)

Por la presente le comunico/comunicamos* que desisto de mi/desistimos de nuestro* contrato de venta del siguiente bien/prestaci�n del siguiente servicio*

Pedido el/recibido el*:

Nombre del consumidor y usuario o de los consumidores y usuarios:

Domicilio del consumidor y usuario o de los consumidores y usuarios:

Firma del consumidor y usuario o de los consumidores y usuarios (solo si el presente formulario se presenta en papel):

Fecha:

* Eliminar en su caso

Condiciones de env�o

Most orders usually ship within 1-3 business days, but some can take up to 7 days.

Tarifas de env�o de Reino Unido a Estados Unidos de America

Tarifas de env�o de Reino Unido a Estados Unidos de America
Cantidad del pedido	De 7 a 28 d�as h�biles	De 7 a 28 d�as h�biles
Primer art�culo	EUR 14.99	EUR 17.30

Los plazos de entrega los establecen los vendedores y var�an seg�n el transportista y la ubicaci�n. Los pedidos que pasan por la aduana pueden sufrir retrasos y los compradores son responsables de los aranceles o tarifas asociadas. Los vendedores pueden ponerse en contacto con usted en relaci�n con cargos adicionales para cubrir cualquier aumento en los costes de env�o de los art�culos.