Estimation of the depth-dependent component of the point spread function of SPECT

The point spread function (PSF) of a gamma camera describes the photon coun t density distribution at the detector surface when a point source is image d. Knowledge of the PSF is important for computer simulation and accurate i mage reconstruction of single photon emission computed tomography (SPECT) i mages. To reduce the number of measurements required for PSF characterizati on and the amount of computer memory to store PSF tables, and to enable gen eralization of the PSF to different collimator-to-source distances, the PSF may be modeled as the two-dimensional (2D) convolution of the depth-depend ent component which is free of detector blurring (pSF(ideal)) and the dista nce-dependent detector response. Owing to limitations imposed by the radioa ctive strength of point sources, extended sources have to be used for measu rements. Therefore, if pSF(ideal) is estimated from measured responses, cor rections have to be made for both the detector blurring and for the extent of the source. In this paper:, an approach based on maximum likelihood expe ctation-maximization (ML-EM) is used to estimate pSF(ideal). In addition, a practical measurement procedure which avoids problems associated with comm only used line-source measurements is proposed. To decrease noise and to pr event nonphysical solutions, shape constraints are applied during the estim ation of pSF(ideal). The estimates are generalized to depths other than tho se which have been measured and are incorporated in a SPECT simulator. The method is validated for Tc-99m and Tl-201 by means of measurements on physi cal phantoms. The corrected responses have the desired shapes and simulated responses closely resemble measured responses. The proposed methodology ma y, consequently, serve as a basis for accurate three-dimensional (3D) SPECT reconstruction. (C) 1999 American Association of Physicists in Medicine. [ S0094-2405(99)01311-5].