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Proceedings Paper

SinoCor: motion correction in SPECT
Author(s): Debasis Mitra; Daniel Eiland; Mahmoud Abdallah; Rostyslav Bouthcko; Grant T. Gullberg; Norberto Schechtmann
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Paper Abstract

Motion is a serious artifact in Cardiac nuclear imaging because the scanning operation takes a long time. Since reconstruction algorithms assume consistent or stationary data the quality of resulting image is affected by motion, sometimes significantly. Even after adoption of the gold standard MoCo(R) algorithm from Cedars-Sinai by most vendors, heart motion remains a significant challenge. Also, any serious study in quantitative analysis necessitates correction for motion artifacts. It is generally recognized that human eye is a very sensitive tool for detecting motion. However, two reasons prevent such manual correction: (1) it is costly in terms of specialist's time, and (2) no such tool for manual correction is available currently. Previously, at SPIE-MIC'11, we presented a simple tool (SinoCor) that allows sinograms to be corrected manually or automatically. SinoCor performs correction of sinograms containing inter-frame patient or respiratory motions using rigid-body dynamics. The software is capable of detecting the patient motion and estimating the body-motion vector using scanning geometry parameters. SinoCor applies appropriate geometrical correction to all the frames subsequent to the frame when the movement has occurred in a manual or automated mode. For respiratory motion, it is capable of automatically smoothing small oscillatory (frame-wise local) movements. Lower order image moments are used to represent a frame and the required rigid body movement compensation is computed accordingly. Our current focus is on enhancement of SinoCor with the capability to automatically detect and compensate for intra-frame motion that causes motion blur on the respective frame. Intra-frame movements are expected in both patient and respiratory motions. For a controlled study we also have developed a motion simulator. A stable version of SinoCor is available under license from Lawrence Berkeley National Laboratory.

Paper Details

Date Published: 24 February 2012
PDF: 5 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 831452 (24 February 2012); doi: 10.1117/12.911101
Show Author Affiliations
Debasis Mitra, Florida Institute of Technology (United States)
Daniel Eiland, Florida Institute of Technology (United States)
Mahmoud Abdallah, Florida Institute of Technology (United States)
Rostyslav Bouthcko, Lawrence Berkeley National Lab. (United States)
Grant T. Gullberg, Lawrence Berkeley National Lab. (United States)
Norberto Schechtmann, MIMA, Melbourne (United States)


Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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