Towards segmentation of the thymus in fat and water parametric MR images

Sokratis Makrogiannis, Ramona Ramachandran, Kenneth W. Fishbein, Dimitrios Kapogiannis, Richard G. Spencer, Chee W. Chia

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

Abstract

The thymus, an organ responsible for the development, selection, and maintenance of the peripheral T-cell population, is an important regulator of the immune system. Despite its physiological significance, it has received little attention in the medical image analysis literature. In practice, the anatomical location and variable shape of this gland pose challenges both in the image acquisition and analysis processes. We present an automated method for segmenting the thymus from water and fat parametric MR images that permits further analysis of volumetrics and tissue characterization. We compute fat ratio and water ratio parametric images and introduce the use of a stochastic edge detector that is embedded in a geometric variational segmentation model. Validation experiments of the proposed algorithm against manual delineations of the thymus indicate the applicability of our approach.

Original languageEnglish (US)
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages8078-8081
Number of pages4
DOIs
StatePublished - 2011
Externally publishedYes
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Publication series

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

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Country/TerritoryUnited States
CityBoston, MA
Period8/30/119/3/11

ASJC Scopus subject areas

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

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