An evaluation of data-driven motion estimation in comparison to the usage of external-surrogates in cardiac SPECT imaging
UMass Chan Affiliations
Department of RadiologyDocument Type
Journal ArticlePublication Date
2013-11-07Keywords
HeartHumans
Image Processing, Computer-Assisted
Monte Carlo Method
*Movement
Myocardial Perfusion Imaging
Phantoms, Imaging
Software
Tomography, Emission-Computed, Single-Photon
Radiology
Metadata
Show full item recordAbstract
Motion estimation methods in single photon emission computed tomography (SPECT) can be classified into methods which depend on just the emission data (data-driven), or those that use some other source of information such as an external surrogate. The surrogate-based methods estimate the motion exhibited externally which may not correlate exactly with the movement of organs inside the body. The accuracy of data-driven strategies on the other hand is affected by the type and timing of motion occurrence during acquisition, the source distribution, and various degrading factors such as attenuation, scatter, and system spatial resolution. The goal of this paper is to investigate the performance of two data-driven motion estimation schemes based on the rigid-body registration of projections of motion-transformed source distributions to the acquired projection data for cardiac SPECT studies. Comparison is also made of six intensity based registration metrics to an external surrogate-based method. In the data-driven schemes, a partially reconstructed heart is used as the initial source distribution. The partially-reconstructed heart has inaccuracies due to limited angle artifacts resulting from using only a part of the SPECT projections acquired while the patient maintained the same pose. The performance of different cost functions in quantifying consistency with the SPECT projection data in the data-driven schemes was compared for clinically realistic patient motion occurring as discrete pose changes, one or two times during acquisition. The six intensity-based metrics studied were mean-squared difference, mutual information, normalized mutual information (NMI), pattern intensity (PI), normalized cross-correlation and entropy of the difference. Quantitative and qualitative analysis of the performance is reported using Monte-Carlo simulations of a realistic heart phantom including degradation factors such as attenuation, scatter and system spatial resolution. Further the visual appearance of motion-corrected images using data-driven motion estimates was compared to that obtained using the external motion-tracking system in patient studies. Pattern intensity and normalized mutual information cost functions were observed to have the best performance in terms of lowest average position error and stability with degradation of image quality of the partial reconstruction in simulations. In all patients, the visual quality of PI-based estimation was either significantly better or comparable to NMI-based estimation. Best visual quality was obtained with PI-based estimation in one of the five patient studies, and with external-surrogate based correction in three out of five patients. In the remaining patient study there was little motion and all methods yielded similar visual image quality.Source
Phys Med Biol. 2013 Nov 7;58(21):7625-46. doi: 10.1088/0031-9155/58/21/7625. Link to article on publisher's siteDOI
10.1088/0031-9155/58/21/7625Permanent Link to this Item
http://hdl.handle.net/20.500.14038/48123PubMed ID
24107647Related Resources
Link to Article in PubMedae974a485f413a2113503eed53cd6c53
10.1088/0031-9155/58/21/7625