Cross-Correlation Template Matching for Liver Localisation in Computed Tomography

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Title: Cross-Correlation Template Matching for Liver Localisation in Computed Tomography
Authors: Leydon, PatrickO'Connell, MartinGreene, DerekCurran, Kathleen M.
Permanent link: http://hdl.handle.net/10197/11362
Date: 30-Jul-2019
Online since: 2020-05-05T10:32:22Z
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.
Funding Details: Science Foundation Ireland
metadata.dc.description.othersponsorship: Insight Research Centre
Type of material: Conference Publication
Keywords: Medical imagingTemplate matchingCross-correlationLocalisationLiver
DOI: 10.21427/8fgf-y086
Other versions: https://arrow.dit.ie/ditpress/11/
http://www.imvip.ie/
Language: en
Status of Item: Peer reviewed
Conference Details: The 2019 Irish Machine Vision and Image Processing Conference (IMVIP 2019), Technological University Dublin, 28-30 August 2019
ISBN: 978 0 9934207 4 0
Appears in Collections:Insight Research Collection

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