An em algorithm for brain tumor image registration: A tumor growth modeling based approach

Ali Gooya, George Biros, Christos Davatzikos

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

Abstract

This paper investigates the problem of atlas registration of brain images with tumors. Multi-parametric imaging modalities are first utilized for segmentations of different tissues, and to compute the posterior probability map (PBM) of membership to each tissue class, using supervised learning. Similar maps are generated in the initially normal atlas, by modeling the tumor growth. An Expectation-Maximization algorithm is used to estimate the spatial transformation and other parameters related to tumor simulation are optimized through Asynchronous Parallel Pattern Search (APPSPACK). The proposed method has been evaluated on simulated data sets created by Statistically Simulated Deformations (SSD), and real multichannel Glioma data sets. The performance has been evaluated both quantitatively and qualitatively. The results show that our method is promising to achieve a good similarity between the warped templates and patient images.

Original languageEnglish (US)
Title of host publication2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
Pages39-46
Number of pages8
DOIs
StatePublished - Sep 17 2010
Event2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010 - San Francisco, CA, United States
Duration: Jun 13 2010Jun 18 2010

Publication series

Name2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010

Other

Other2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
CountryUnited States
CitySan Francisco, CA
Period6/13/106/18/10

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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    Gooya, A., Biros, G., & Davatzikos, C. (2010). An em algorithm for brain tumor image registration: A tumor growth modeling based approach. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010 (pp. 39-46). [5543440] (2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010). https://doi.org/10.1109/CVPRW.2010.5543440