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Shape Analysis in Medical Image Analysis

  • Shuo Li
  • João Manuel R. S. Tavares

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

  • 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
  • Print ISBN 978-3-319-03812-4
  • Online ISBN 978-3-319-03813-1
  • Series Print ISSN 2212-9391
  • Series Online ISSN 2212-9413
  • Buy this book on publisher's site
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