Automatic Prior Shape Selection for Image Segmentation

Weihong Guo; Jing Qin; Sibel Tari

doi:10.1007/978-3-319-16348-2_1

Automatic Prior Shape Selection for Image Segmentation

Weihong Guo, Jing Qin, Sibel Tari

Mathematics

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

3 Scopus citations

Abstract

Segmenting images with occluded and missing intensity information is still a difficult task. Intensity based segmentation approaches often lead to wrong results. High vision prior information such as prior shape has been proven to be effective in solving this problem. Most existing shape prior approaches assume known prior shape and segmentation results rely on the selection of prior shape. In this paper, we study how to do simultaneous automatic prior shape selection and segmentation in a variational scheme.

Original language	English
Title of host publication	Association for Women in Mathematics Series
Pages	1-8
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-319-16348-2_1
State	Published - 2015

Publication series

Name	Association for Women in Mathematics Series
Volume	1
ISSN (Print)	2364-5733
ISSN (Electronic)	2364-5741

Bibliographical note

Publisher Copyright:
© 2015, Springer International Publishing Switzerland & The Association for Women in Mathematics.

Funding

Acknowledgements The authors would like to thank Luminita Vese from the Department of Mathematics at the University of California, Los Angeles for insightful discussions. The joint research is partially funded via US NIH 1R21EB016535-01 to W.G. and TUBITAK 112E208 to S.T.

Funders	Funder number
TUBITAK	112E208
National Institutes of Health (NIH)	1R21EB016535-01

Keywords

Base Segmentation Model
Data Fidelity Term
Image Segmentation
Prior Shape
Sparse Optimization

ASJC Scopus subject areas

General Mathematics
Gender Studies

Access to Document

10.1007/978-3-319-16348-2_1

Cite this

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AU - Tari, Sibel

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KW - Data Fidelity Term

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KW - Prior Shape

KW - Sparse Optimization

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ER -

Automatic Prior Shape Selection for Image Segmentation

Abstract

Publication series

Bibliographical note

Funding

Keywords

ASJC Scopus subject areas

Access to Document

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