Mining pattern sequences in respiratory tumor motion data

Arvind Balasubramanian, Balakrishnan Prabhakaran, Amit Sawant

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

3 Scopus citations

Abstract

Management of respiration induced tumor motion during radiation therapy is crucial to effective treatment. Pattern sequences in the tumor motion signals can be valuable features in the analysis and prediction of irregular tumor motion. In this study, we put forward an approach towards mining pattern sequences in respiratory tumor motion data. We discuss the use of pattern sequence distributions as effective representations of motion characteristics, and find similarities between individual tumor motion instances. We also explore grouping of patients based on similarities in pattern sequence distributions exhibited by their respiratory motion traces.

Original languageEnglish (US)
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages5262-5265
Number of pages4
DOIs
StatePublished - Dec 14 2012
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Country/TerritoryUnited States
CitySan Diego, CA
Period8/28/129/1/12

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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