Skip to main content
SpringerLink
Log in

A Probabilistic Framework for Point-Based Shape Modeling in Medical Image Analysis

  • Book
  • © 2011

Overview

Authors:
  1. Heike Hufnagel
    View author publications

    You can also search for this author in PubMed   Google Scholar

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (6 chapters)

  1. Front Matter

    Pages i-xxiii
    Download chapter PDF

  2. Introduction

    • Heike Hufnagel
    Pages 1-5

  3. Current Methods in Statistical Shape Analysis

    • Heike Hufnagel
    Pages 7-25

  4. A Generative Gaussian Mixture Statistical Shape Model

    • Heike Hufnagel
    Pages 27-55

  5. Evaluation of the GGM-SSM

    • Heike Hufnagel
    Pages 57-80

  6. Using the GGM-SSM as a Prior for Segmentation

    • Heike Hufnagel
    Pages 81-113

  7. Conclusion

    • Heike Hufnagel
    Pages 115-120

  8. Back Matter

    Pages 121-147
    Download chapter PDF
Back to top

Keywords

About this book

In medical image analysis, major areas such as radiotherapy, surgery planning, and quantitative diagnostics benefit from shape modeling to facilitate solutions to analysis, segmentation and reconstruction problems.
Heike Hufnagel proposes a mathematically sound statistical shape model using correspondence probabilities instead of 1-to-1 correspondences. The explicit probabilistic model is employed as shape prior in an implicit level set segmentation. Due to the particular attributes of the new model, the challenging integration of explicit and implicit representations can be done in an elegant mathematical formulation, thus combining the advantages of both explicit model and implicit segmentation. Evaluations are performed to depict the characteristics and strengths of the new model and segmentation method.

The dissertation has received the Fokusfinder award 2011 by the Innovationsstiftung Schleswig-Holstein (ISH), the Basler AG and Philips Medical Systems.

About the author

Heike Hufnagel works as a research scientist at the Institute of Medical Informatics, University of Luebeck, Germany. She holds a PhD in natural sciences.

Bibliographic Information

  • Book Title: A Probabilistic Framework for Point-Based Shape Modeling in Medical Image Analysis

  • Authors: Heike Hufnagel

  • Series Title: Aktuelle Forschung Medizintechnik – Latest Research in Medical Engineering

  • DOI: https://doi.org/10.1007/978-3-8348-8600-2

  • Publisher: Vieweg+Teubner Verlag Wiesbaden

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Vieweg+Teubner Verlag | Springer Fachmedien Wiesbaden GmbH, Wiesbaden 2011

  • Softcover ISBN: 978-3-8348-1722-8Published: 19 September 2011

  • eBook ISBN: 978-3-8348-8600-2Published: 23 November 2011

  • Series ISSN: 2625-9354

  • Series E-ISSN: 2625-9362

  • Edition Number: 1

  • Number of Pages: XXIII, 147

  • Number of Illustrations: 53 b/w illustrations

  • Topics: Biomedical Engineering and Bioengineering

Publish with us

Policies and ethics

Back to top

Search

Navigation