Ultrasound image analysis for myopathy detection

Seth Billings, Jemima Albayda, Philippe Burlina

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

Abstract

This study focuses on using ultrasound (US) biomarkers for characterizing myopathies and in particular myositis. US offers an opportunity to deliver diagnostics in clinical settings at a fraction of the cost and discomfort entailed in current workflows. US is also better suited for usage in under-resourced environments. This paper is focused on studying the link between biomarkers related to absolute and relative echo intensity of muscle tissue and the presence and severity of myositis disease. We show that there is good correlation between these biomarkers and the severity of muscle disease rated by the Heckmatt criteria. A moderate correlation is also found between these biomarkers and muscles categorized by healthy vs. diseased status of each patient. Experimental data involving 37 patients (9 polymyositis, 3 dermatomyositis, 9 inclusion body myositis, and 16 healthy patients) and seven muscle groups show correlations up to 0.91.

Original languageEnglish (US)
Title of host publication2016 23rd International Conference on Pattern Recognition, ICPR 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1461-1465
Number of pages5
ISBN (Electronic)9781509048472
DOIs
StatePublished - Jan 1 2016
Event23rd International Conference on Pattern Recognition, ICPR 2016 - Cancun, Mexico
Duration: Dec 4 2016Dec 8 2016

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume0
ISSN (Print)1051-4651

Other

Other23rd International Conference on Pattern Recognition, ICPR 2016
CountryMexico
CityCancun
Period12/4/1612/8/16

Keywords

  • Image biomarkers
  • Myopathy
  • Myositis
  • Regression
  • Ultrasound

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Billings, S., Albayda, J., & Burlina, P. (2016). Ultrasound image analysis for myopathy detection. In 2016 23rd International Conference on Pattern Recognition, ICPR 2016 (pp. 1461-1465). [7899843] (Proceedings - International Conference on Pattern Recognition; Vol. 0). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPR.2016.7899843