Image-based reconstruction of 3D myocardial infarct geometry for patient specific applications

Eranga Ukwatta; Martin Rajchl; James White; Farhad Pashakhanloo; Daniel A. Herzka; Elliot McVeigh; Albert C. Lardo; Natalia Trayanova; Fijoy Vadakkumpadan

doi:10.1117/12.2082113

20 March 2015 Image-based reconstruction of 3D myocardial infarct geometry for patient specific applications

Eranga Ukwatta, Martin Rajchl, James White, Farhad Pashakhanloo, Daniel A. Herzka, Elliot McVeigh, Albert C. Lardo, Natalia Trayanova, Fijoy Vadakkumpadan

Author Affiliations +

Proceedings Volume 9413, Medical Imaging 2015: Image Processing; 94132W (2015) https://doi.org/10.1117/12.2082113
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

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.

Citation Download Citation

Eranga Ukwatta, Martin Rajchl, James White, Farhad Pashakhanloo, Daniel A. Herzka, Elliot McVeigh, Albert C. Lardo, Natalia Trayanova, and Fijoy Vadakkumpadan "Image-based reconstruction of 3D myocardial infarct geometry for patient specific applications", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94132W (20 March 2015); https://doi.org/10.1117/12.2082113

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available