Motion-compensated post-processing of gated cardiac SPECT images using a deformable mesh model

Thibault Marin; Miles N. Wernick; Yongyi Yang; Jovan G. Brankov

doi:10.1117/12.812133

27 March 2009 Motion-compensated post-processing of gated cardiac SPECT images using a deformable mesh model

Thibault Marin, Miles N. Wernick, Yongyi Yang, Jovan G. Brankov

Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 72592E (2009) https://doi.org/10.1117/12.812133
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

We present a post-reconstruction motion-compensated spatio-temporal filtering method for noise reduction in cardiac gated SPECT images. SPECT imaging suffers from low photon count due to radioactive dose limitations resulting in a high noise level in the reconstructed images. This is especially true in gated cardiac SPECT where the total number of counts is divided into a number of gates (time frames). Classical spatio-temporal filtering approaches, used in gated cardiac SPECT for noise reduction, do not accurately account for myocardium motion and brightening and therefore perform sub-optimally. The proposed post-reconstruction method consists of two steps: motion and brightening estimation and spatio-temporal motion-compensated filtering. In the first step we utilize a left ventricle model and a deformable mesh structure. The second step, which consists of motion-compensated spatio-temporal filtering, makes use of estimated myocardial motion to enable accurate smoothing. Additionally, the algorithm preserves myocardial brightening, a result of partial volume effect which is widely used as a diagnostic feature. The proposed method is evaluated quantitatively to assess noise reduction and the influence on estimated ejection fraction.

Citation Download Citation

Thibault Marin, Miles N. Wernick, Yongyi Yang, and Jovan G. Brankov "Motion-compensated post-processing of gated cardiac SPECT images using a deformable mesh model", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72592E (27 March 2009); https://doi.org/10.1117/12.812133

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