Computational models for small experimental animals are important in medical imaging and radiation dosimetry researches. The boundary representation method by use of nonuniform rational B-splines (NURBS) is adopted in this paper to develop a rat computational phantom based on the previously obtained segmentation data for cryosectional color photographic images of an adult male Sprague-Dawley rat. Continuous two-dimensional contours for a total of 14 major structures were outlined from the downscaled anatomical atlas, corresponding to a voxel size of 0.2 times 0.2 times 0.2 mm3and stacked to reconstruct the three-dimensional (3-D) shapes. The NURBS model was then appropriately fitted through the surface of each organ. Monte Carlo simulation of cone beam X-ray computed tomography was performed focusing on the thorax region to demonstrate the usefulness of the computational phantom in radiological imaging. The integrated whole-body geometry is presented with smooth internal and exterior boundaries. Organ centroid coordinates and volume information are tabulated for future comparison purposes. The rat phantom can be used in 3-D dose calculation and other computational applications as well.

Accurate reconstruction of SPECT images is hampered by four nonlinear effects in the acquisition process: attenuation, scatter, collimator acceptance angle, and statistical noise. A good mathematical description of these effects is obviously crucial for the reconstruction. Poisson noise, attenuation, and collimator acceptance angle are relatively easy to model. Scattering, however, is a very complex process, and is mostly described using empirical models. A new model for the scatter point spread function in a homogeneous medium that is based on physical considerations and is capable of predicting scatter contributions of point sources as a function of depth in homogeneous media is presented. The model is verified with Monte Carlo simulations and line source measurements, and is compared to an existing empirical model.