An information theoretic approach via IJM to segmenting MR images with MS lesions

Jason E. Hill, Brian Nutter, Sunanda Mitra

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

Abstract

Automated detection of brain pathologies from Magnetic Resonance (MR) images remains an outstanding problem. An information theoretic approach for automated segmentation of medical images called the Improved 'Jump' Method (IJM) has been recently developed and validated. Here we extend this work by utilizing IJM to segment human brain MR images with multiple-sclerosis (MS) lesions in order to probe IJM's limitations and versatility.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE 27th International Symposium on Computer-Based Medical Systems, CBMS 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages189-192
Number of pages4
ISBN (Print)9781479944354
DOIs
StatePublished - 2014
Event27th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2014 - New York, NY, United States
Duration: May 27 2014May 29 2014

Publication series

NameProceedings - IEEE Symposium on Computer-Based Medical Systems
ISSN (Print)1063-7125

Conference

Conference27th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2014
CountryUnited States
CityNew York, NY
Period05/27/1405/29/14

Keywords

  • information theory
  • model order estimation
  • segmentation

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  • Cite this

    Hill, J. E., Nutter, B., & Mitra, S. (2014). An information theoretic approach via IJM to segmenting MR images with MS lesions. In Proceedings - 2014 IEEE 27th International Symposium on Computer-Based Medical Systems, CBMS 2014 (pp. 189-192). [6881874] (Proceedings - IEEE Symposium on Computer-Based Medical Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CBMS.2014.130