Elsevier are delighted to announce the latest books in the MICCAI series

Wednesday, July 26, 2017

Depeursinge et al: Biomedical Texture Analysis August 2017

Provides the fundamentals and applications of biomedical texture analysis
Uses recent open-source software frameworks which enable the extraction, exploration and analysis of 2D and 3D texture-based imaging biomarkers
Contains examples of novel texture operators

Dalca et al: Imaging Genetics September 2017

Contains an introduction describing how the field has evolved to the present, together with perspectives on its future direction and challenges
Describes novel application domains and analytic methods that represent the state-of-the-art in the burgeoning field of imaging genetics
Introduces a novel, large-scale analytic framework that involves multi-site, image-wide, genome-wide associations

Members of MICCAI can save up to 30% on the books and ebooks in the series at Elsevier.com. Enter code MICCAI30 to claim your discount and get free shipping!

Zhou et al: Deep Learning for Medical Image Analysis

Covers common research problems in medical image analysis and their challenges
Describes 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 Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc.
Includes a Foreword written by Nicholas Ayache

To find out more about the book and the authors, read an interview here:

Zhou: Medical Image Recognition, Segmentation and Parsing

Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects
Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets
Includes algorithms for recognizing and parsing of known anatomies for practical applications

Wu: Machine Learning and Medical Imaging

Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems
Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics
Features self-contained chapters with a thorough literature review
Assesses the development of future machine learning techniques and the further application of existing techniques

Balocco: Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting

Brings together scientific researchers, medical experts, and industry partners working in different anatomical regions
Presents an introduction to the clinical workflow and current challenges in endovascular Interventions
Provides a review of the state-of-the-art methodologies in endovascular imaging and their applications
Poses outstanding questions and discusses future research



If you're interested in writing or editing a book in the series please contact:

Alex Frangi, University of Sheffield UK and Book Series Editorial Board Chair, a.frangi@sheffield.ac.uk
Tim Pitts, Acquisitions Editor at Elsevier: tim.pitts@elsevier.com