Patient-specific three-dimensional torso models for analysing cardiac activity

Vanheusden, FJ ORCID: https://orcid.org/0000-0003-2369-6189, Salinet, JL, Nicolson, WB, McCann, GP, Ng, GA and Schlindwein, FS, 2012. Patient-specific three-dimensional torso models for analysing cardiac activity. In: Murray, A, ed., Computing in Cardiology 2012. Computing in Cardiology, 39 . Piscataway, N.J.: IEEE, pp. 973-976. ISBN 9781467320740

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Abstract

Standard electrocardiogram (ECG) is routinely used for recording cardiac electrical activity but lacks 3D details. Body surface potential mapping techniques have been developed more recently. A major challenge related to this technique is the projection of body signals back to their original sources in the heart. For an accurate projection, one needs to take into account patient-specific electrophysiological data of tissues surrounding the heart. Much information regarding physiological variations, as well as the exact position of organs in the torso, can be obtained from magnetic resonance (MR) images. Here, a patient-specific methodology for building 3D torso models from transverse MR images is proposed. Torso contour detection is based on edge detection using a canny filter and indicating contour points with a polar coordinate system. Organ detection is performed using an interpolation technique with Active Contour modelling. Results show that accurate torso models can be constructed with short processing time.

Item Type:	Chapter in book
Description:	Paper presented at 2012 Computing in Cardiology Conference (CinC), Kraków, Poland, 9-12 September 2012.
Creators:	Vanheusden, F.J., Salinet, J.L., Nicolson, W.B., McCann, G.P., Ng, G.A. and Schlindwein, F.S.
Publisher:	IEEE
Place of Publication:	Piscataway, N.J.
Date:	September 2012
Volume:	39
ISBN:	9781467320740
ISSN:	2325-8861
Rights:	Articles in this volume are copyright (C) 2012 by their respective authors, and are licensed by their authors under the Creative Commons Attribution License 2.5 (CCAL).
Divisions:	Schools > School of Science and Technology
Record created by:	Jill Tomkinson
Date Added:	12 Dec 2018 11:46
Last Modified:	12 Dec 2018 17:17
URI:	https://irep.ntu.ac.uk/id/eprint/35304

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