Advertisement

© 2014

Shape Analysis in Medical Image Analysis

  • Shuo Li
  • João Manuel R. S. Tavares

Benefits

  • First book to cover this topic in the field so comprehensively

  • Detailed attention is given to sub-topics too

  • Medical imaging is a topic that affects many and has wide applications

Book

Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 14)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Methods and Models

    1. Front Matter
      Pages 1-1
    2. Bernard Ng, Matthew Toews, Stanley Durrleman, Yonggang Shi
      Pages 3-49
    3. Fei Gao, Pengcheng Shi
      Pages 51-93
    4. Amal A. Farag, Ahmed Shalaby, Hossam Abd El Munim, Aly Farag
      Pages 95-121
    5. Zhong Xue, Stephen Wong
      Pages 123-149
    6. Jürgen Weese, Irina Wächter-Stehle, Lyubomir Zagorchev, Jochen Peters
      Pages 151-184
  3. Application Cases

    1. Front Matter
      Pages 185-185
    2. April Khademi, Alan R. Moody, Anastasios Venetsanopoulos
      Pages 187-227
    3. Amal A. Farag, Mostafa Farag, James Graham, Salwa Elshazly, Mohamed al Mogy, Aly Farag
      Pages 259-290
    4. Jianming Liang, Tim McInerney, Demetri Terzopoulos
      Pages 291-314
    5. Alberto Santamaria-Pang, Yuchi Huang, Zhengyu Pang, Li Qing, Jens Rittscher
      Pages 315-338
    6. Tobias Klinder, Samuel Kadoury, Cristian Lorenz
      Pages 339-371
    7. Vahid Tavakoli, Nirmanmoh Bhatia, Rita Longaker, Motaz Alshaher, Marcus Stoddard, Amir A. Amini
      Pages 413-440
  4. Back Matter
    Pages 441-442

About this book

Introduction

This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification, and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice.

This volume treats topics such as, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms.

This work will be of interest to researchers, students, and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computational vision, computer sciences, human motion, mathematics, medical imaging, medicine, pattern recognition and physics.

 

Keywords

Machine Learning for Shape Modeling and Analysis Modeling Algorithms Shape Based Medical Image Segmentation Shape Representation, Modeling and Analysis Validation

Editors and affiliations

  • Shuo Li
    • 1
  • João Manuel R. S. Tavares
    • 2
  1. 1.GE Healthcare and University of Western OntarioLondonCanada
  2. 2.Departamento de Engenharia MecânicaUniversidade do PortoPortoPortugal

Bibliographic information

  • Book Title Shape Analysis in Medical Image Analysis
  • Editors Shuo Li
    João Manuel R. S. Tavares
  • Series Title Lecture Notes in Computational Vision and Biomechanics
  • Series Abbreviated Title Lect. Notes Computational Vision
  • DOI https://doi.org/10.1007/978-3-319-03813-1
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-319-03812-4
  • Softcover ISBN 978-3-319-37521-2
  • eBook ISBN 978-3-319-03813-1
  • Series ISSN 2212-9391
  • Series E-ISSN 2212-9413
  • Edition Number 1
  • Number of Pages VIII, 442
  • Number of Illustrations 220 b/w illustrations, 0 illustrations in colour
  • Topics Biomedical Engineering and Bioengineering
    Image Processing and Computer Vision
    Imaging / Radiology
  • Buy this book on publisher's site
Industry Sectors
Health & Hospitals
Biotechnology
Electronics
Consumer Packaged Goods
Engineering
Pharma
Materials & Steel