Edical Image Analysis
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Deep Learning for Medical Image Analysis
Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis. - Covers common research problems in medical image analysis and their challenges - Describes the latest deep learning methods and the theories behind approaches for medical image analysis - Teaches how algorithms are applied to a broad range of application areas including cardiac, neural and functional, colonoscopy, OCTA applications and model assessment· Includes a Foreword written by Nicholas Ayache
Medical Image Analysis
The expanded and revised edition will split Chapter 4 to include more details and examples in FMRI, DTI, and DWI for MR image modalities. The book will also expand ultrasound imaging to 3-D dynamic contrast ultrasound imaging in a separate chapter. A new chapter on Optical Imaging Modalities elaborating microscopy, confocal microscopy, endoscopy, optical coherent tomography, fluorescence and molecular imaging will be added. Another new chapter on Simultaneous Multi-Modality Medical Imaging including CT-SPECT and CT-PET will also be added. In the image analysis part, chapters on image reconstructions and visualizations will be significantly enhanced to include, respectively, 3-D fast statistical estimation based reconstruction methods, and 3-D image fusion and visualization overlaying multi-modality imaging and information. A new chapter on Computer-Aided Diagnosis and image guided surgery, and surgical and therapeutic intervention will also be added. A companion site containing power point slides, author biography, corrections to the first edition and images from the text can be found here: wiley.com/public/sci_tech_med/medical_image/ Send an email to: [email protected] to obtain a solutions manual. Please include your affiliation in your email.
Computer Vision Approaches to Medical Image Analysis
Author: Reinhard R. Beichel
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-09-29
This book constitutes the thoroughly refereed post proceedings of the international workshop Computer Vision Approaches to Medical Image Analysis, CVAMIA 2006, held in Graz, Austria in May 2006 as a satellite event of the 9th European Conference on Computer Vision, EECV 2006. The 10 revised full papers and 11 revised poster papers presented together with one invited talk were carefully reviewed and selected from 38 submissions.