Soft tissue discrimination using magnetic resonance elastography with a new elastic level set model

Bing Nan Li, Chee Kong Chui, Sim Heng Ong, Toshikatsu Washio, Tomokazu Numano, Stephen Chang, Sudhakar Venkatesh, Etsuko Kobayashi

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

1 Scopus citations

Abstract

Magnetic resonance elastography (MRE) noninvasively images the propagation of mechanical waves within soft tissues. The elastic properties of soft tissues can then be quantified from MRE wave snapshots. Various algorithms have been proposed to obtain their inversion for soft tissue elasticity. Anomalies are assumed to be discernible in the elasticity map. We propose a new elastic level set model to directly detect and track abnormal soft tissues in MRE wave images. It is derived from the Mumford-Shah functional, and employs partial differential equations for function modeling and smoothing. This level set model can interpret MRE wave images without elasticity reconstruction. The experimental results on synthetic and real MRE wave images confirm its effectiveness for soft tissue discrimination.

Original languageEnglish (US)
Title of host publicationMachine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings
Pages76-83
Number of pages8
DOIs
StatePublished - Oct 25 2010
Event1st International Workshop on Machine Learning in Medical Imaging, MLMI 2010, Held in Conjunction with MICCAI 2010 - Beijing, China
Duration: Sep 20 2010Sep 20 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6357 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Workshop on Machine Learning in Medical Imaging, MLMI 2010, Held in Conjunction with MICCAI 2010
CountryChina
CityBeijing
Period9/20/109/20/10

Keywords

  • Elastic imaging
  • level set methods
  • magnetic resonance elastography (MRE)
  • medical image segmentation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Li, B. N., Chui, C. K., Ong, S. H., Washio, T., Numano, T., Chang, S., Venkatesh, S., & Kobayashi, E. (2010). Soft tissue discrimination using magnetic resonance elastography with a new elastic level set model. In Machine Learning in Medical Imaging - First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Proceedings (pp. 76-83). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6357 LNCS). https://doi.org/10.1007/978-3-642-15948-0_10