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Cross-Correlation Template Matching for Liver Localisation in Computed Tomography

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Author(s)
Leydon, Patrick 
O'Connell, Martin 
Greene, Derek 
Curran, Kathleen M. 
Uri
http://hdl.handle.net/10197/11362
Date Issued
30 July 2019
Date Available
05T10:32:22Z May 2020
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. CrossCorrelation, 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.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Insight Research Centre
Type of Material
Conference Publication
Keywords
  • Medical imaging

  • Template matching

  • Cross-correlation

  • Localisation

  • Liver

DOI
10.21427/8fgf-y086
Web versions
https://arrow.dit.ie/ditpress/11/
http://www.imvip.ie/
Language
English
Status of Item
Peer reviewed
Description
The 2019 Irish Machine Vision and Image Processing Conference (IMVIP 2019), Technological University Dublin, 28-30 August 2019
ISBN
978 0 9934207 4 0
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Insight Research Collection
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Jan 28, 2023
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