Body Deformation Correction for SPECT Imaging

• Published in: IEEE transactions on nuclear science Vol. 57; no. 1; pp. 214 - 224
• Main Authors: Songxiang Gu, McNamara, J.E., Mitra, J., Gifford, H.C., Johnson, K., Gennert, M.A., King, M.A.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-02-2010; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Abdomen; Bend; Biomedical imaging; Cameras; Computer simulation; Deformable models; Deformation; Degradation; Image reconstruction; Imaging; Markers; Mathematical models; Medical diagnostic imaging; motion correction; Parameter estimation; Patients; Reconstruction; Single photon emission computed tomography; single photon emission computed tomography (SPECT); Tracking; twist
• ISSN: 0018-9499; 1558-1578
• DOI: 10.1109/TNS.2009.2031114

Patient motion degrades the quality of SPECT studies. Body bend and twist are types of patient deformation, which may occur during SPECT imaging, and which has been generally ignored in SPECT motion correction strategies. To correct for these types of motion, we propose a deformation model and its inclusion within an iterative reconstruction algorithm. Two experiments were conducted to investigate the applicability of our model. In the first experiment, the return of the postmotion-compensation locations of markers on the body-surface of a volunteer to approximate their original coordinates is used to examine our method of estimating the parameters of our model and the parameters' use in undoing deformation. The second experiment employed simulated projections of the MCAT phantom formed using an analytical projector which includes attenuation and distance-dependent resolution to investigate applications of our model in reconstruction. We demonstrate in the simulation studies that twist and bend can significantly degrade SPECT image quality visually. Our correction strategy is shown to be able to greatly diminish the degradation seen in the slices, provided the parameters are estimated accurately. We view this work as a first step towards being able to estimate and correct patient deformation based on information obtained from marker tracking data.