2D-PCA based statistical shape model from few medical samples

Tomoko Tateyama, Hossein Foruzan, Yen Wei Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Statistical shape model (SSM) is to model the shape variation of an object. In this paper, we propose an efficient shape representation method and a new 2D-PCA based statistical shape modeling. In our proposed method, we used the radii of these surface points as shape feature instead of their coordinates, and the shape is represented by a 2D matrices. We then apply 2D-PCA to construct a statistical shape model with generalization even from fewer samples.

Original languageEnglish
Title of host publicationIIH-MSP 2009 - 2009 5th International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Pages1266-1269
Number of pages4
DOIs
Publication statusPublished - 2009
Externally publishedYes
EventIIH-MSP 2009 - 2009 5th International Conference on Intelligent Information Hiding and Multimedia Signal Processing - Kyoto, Japan
Duration: 12-09-200914-09-2009

Publication series

NameIIH-MSP 2009 - 2009 5th International Conference on Intelligent Information Hiding and Multimedia Signal Processing

Conference

ConferenceIIH-MSP 2009 - 2009 5th International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Country/TerritoryJapan
CityKyoto
Period12-09-0914-09-09

All Science Journal Classification (ASJC) codes

  • General Computer Science

Fingerprint

Dive into the research topics of '2D-PCA based statistical shape model from few medical samples'. Together they form a unique fingerprint.

Cite this