Leydon, PatrickPatrickLeydonO'Connell, MartinMartinO'ConnellGreene, DerekDerekGreeneCurran, Kathleen M.Kathleen M.Curran2020-05-052020-05-052019-07-30978 0 9934207 4 0http://hdl.handle.net/10197/11362The 2019 Irish Machine Vision and Image Processing Conference (IMVIP 2019), Technological University Dublin, 28-30 August 2019Many 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.enMedical imagingTemplate matchingCross-correlationLocalisationLiverConference Publication10.21427/8fgf-y0862019-10-31https://creativecommons.org/licenses/by-nc-nd/3.0/ie/