Cross-correlation Template Matching for Liver Localisation in Computed Tomography

Patrick Leyden, Martin O'Connell, Derek Greene, Kathleen Curran

Research output: Contribution to conferencePaperpeer-review

Abstract

Many of the current approaches to automatic organ localisation in medical imaging require a large amount of labelled patient data to train systems to accurately identify specific anatomical features. Cross- Correlation, also known as template matching, is a statistical method of assessing the similarity between a template image and a target image. This method has been modified and presented here to localize the liver in Computed Tomography volume images in the Coronal and Sagital planes to achieve a mean positioning error of approximately 11 mm and 20 mm respectively based on between 1 and 25 datasets to create the template liver.
Original languageEnglish
DOIs
Publication statusPublished - 1 Jan 2019
Externally publishedYes
EventIMVIP 2019: Irish Machine Vision & Image Processing - Technological University Dublin, Dublin, Ireland
Duration: 28 Aug 201930 Aug 2019

Conference

ConferenceIMVIP 2019: Irish Machine Vision & Image Processing
Country/TerritoryIreland
CityDublin
Period28/08/1930/08/19

Keywords

  • automatic organ localisation
  • medical imaging
  • template matching
  • liver
  • Computed Tomography
  • Coronal plane
  • Sagital plane
  • positioning error

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