Desiccation diagnosis in lumbar discs from clinical mri with a probabilistic model

Raja S. Alomari, Jason J. Corso, Vipin Chaudhary, Gurmeet Dhillon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

26 Scopus citations

Abstract

Lumbar intervertebral disc diseases are among the main causes of lower back pain (LBP). Desiccation is a common disease resulting from various reasons and ultimately most people are affected by desiccation at some age. We propose a probabilistic model that incorporates intervertebral disc appearance and contextual information for automating the diagnosis of lumbar disc desiccation. We utilize a Gibbs distribution for processing localized lumbar intervertebral discs' appearance and contextual information. We use 55 clinical T2-weighted MRI for lumbar area and achieve over 96% accuracy on a cross validation experiment.

Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2009
Pages546-549
Number of pages4
DOIs
StatePublished - 2009
Event2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 - Boston, MA, United States
Duration: 28 Jun 20091 Jul 2009

Publication series

NameProceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Conference

Conference2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009
Country/TerritoryUnited States
CityBoston, MA
Period28/06/091/07/09

Keywords

  • Computer aided diagnosis
  • Desiccation diagnosis
  • Lumbar discs
  • MRI

Fingerprint

Dive into the research topics of 'Desiccation diagnosis in lumbar discs from clinical mri with a probabilistic model'. Together they form a unique fingerprint.

Cite this