- Poster presentation
- Open Access
Fully-automatic synthesis of cine viability CMR images with minimal estimation error
© Hassanein et al; licensee BioMed Central Ltd. 2015
- Published: 3 February 2015
- Tracking Error
- Wall Motion Abnormality
- Circumferential Strain
- Motion Field
- Image Analysis Technique
A typical CMR exam includes cine, tagging, and delayed-hyperenhancement (DHE) sequences to produce images for evaluating global heart function, myocardial contractility, and viability, respectively. Usually, DHE imaging is conducted at mid-diastole. Nevertheless, obtaining cine DHE images is appealing to obtain simultaneous information about tissue viability and wall motion abnormality. In this study, we compare the performance of four image analysis techniques for generating the cine DHE images based on estimating tissue motion, validate the results on numerical phantom, and implement on in-vivo images.
A numerical phantom of a grid-tagged short-axis slice, that experiences cyclic deformation, was built to test the performance of four techniques for estimating the motion field used to generate the cine DHE images: harmonic phase (HARP), and three optical-flow (OF) methods[2–4]: Lucas-Kanade optical-flow (LKOF), Horn-Shunck (HSOF), and band-pass (BPOF). The generated motion fields are compared to the ground-truth motion.
Cine, DHE, and tagged images were acquired from four patients with myocardial infarction (MI) on 3T scanner. The motion field was estimated from the tagged images and used to reconstruct cine DHE images starting from the acquired (known) DHE image. Wall thickening was measured from both cine and generated DHE images. MI was determined using full-width at half-maximum method. Circumferential strain was measured from the tagged images using Diagnosoft software.
BPOF has minimal error in tracking taglines and measuring motion field, which can be used for generating cine DHE images. The generated cine DHE images may be important for comprehensive evaluation of the patient's condition, as they show simultaneous myocardial viability and wall motion abnormality on the same dataset without additional scan time or misregistration problems.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.