Share Email Print

Proceedings Paper

Image-based reconstruction of 3D myocardial infarct geometry for patient specific applications
Author(s): Eranga Ukwatta; Martin Rajchl; James White; Farhad Pashakhanloo; Daniel A. Herzka; Elliot McVeigh; Albert C. Lardo; Natalia Trayanova; Fijoy Vadakkumpadan
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Accurate reconstruction of the three-dimensional (3D) geometry of a myocardial infarct from two-dimensional (2D) multi-slice image sequences has important applications in the clinical evaluation and treatment of patients with ischemic cardiomyopathy. However, this reconstruction is challenging because the resolution of common clinical scans used to acquire infarct structure, such as short-axis, late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) images, is low, especially in the out-of-plane direction. In this study, we propose a novel technique to reconstruct the 3D infarct geometry from low resolution clinical images. Our methodology is based on a function called logarithm of odds (LogOdds), which allows the broader class of linear combinations in the LogOdds vector space as opposed to being limited to only a convex combination in the binary label space. To assess the efficacy of the method, we used high-resolution LGE-CMR images of 36 human hearts in vivo, and 3 canine hearts ex vivo. The infarct was manually segmented in each slice of the acquired images, and the manually segmented data were downsampled to clinical resolution. The developed method was then applied to the downsampled image slices, and the resulting reconstructions were compared with the manually segmented data. Several existing reconstruction techniques were also implemented, and compared with the proposed method. The results show that the LogOdds method significantly outperforms all the other tested methods in terms of region overlap.

Paper Details

Date Published: 20 March 2015
PDF: 7 pages
Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94132W (20 March 2015); doi: 10.1117/12.2082113
Show Author Affiliations
Eranga Ukwatta, Johns Hopkins Univ. (United States)
Martin Rajchl, Imperial College London (United Kingdom)
James White, Univ. of Calgary (Canada)
Farhad Pashakhanloo, Johns Hopkins Univ. (United States)
Daniel A. Herzka, Johns Hopkins Univ. (United States)
Elliot McVeigh, Johns Hopkins Univ. (United States)
Albert C. Lardo, Johns Hopkins Univ. (United States)
Natalia Trayanova, Johns Hopkins Univ. (United States)
Fijoy Vadakkumpadan, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 9413:
Medical Imaging 2015: Image Processing
Sébastien Ourselin; Martin A. Styner, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?