In this article the authors build on their past attempts to reconstruct a 3D, time-varying bolus of radiotracer from first-pass data obtained by the dynamic SPECT imager, FASTSPECT, built by the University of Arizona. The object imaged is a CardioWest total artificial heart. The bolus is entirely contained in one ventricle and its associated inlet and outlet tubes. The model for the radiotracer distribution at a given time is a closed surface parameterized by 482 vertices that are connected to make 960 triangles, with nonuniform intensity variations of radiotracer allowed inside the surface on a voxel-to-voxel basis. The total curvature of the surface is minimized through the use of a weighted prior in the Bayesian framework, as is the weighted norm of the gradient of the voxellated grid. MAP estimates for the vertices, interior intensity voxels and background count level are produced. The strength of the priors, or hyperparameters, are determined by maximizing the probability of the data given the hyperparameters, called the evidence. The evidence is calculated by first assuming that the posterior is approximately normal in the values of the vertices and voxels, and then by evaluating the integral of the multi-dimensional normal distribution. This integral (which requires …

This paper presents the results of a pilot study whose primary objective was to further substantiate the efficacy of front-end data reduction in computer-aided diagnosis (CAD) of mammograms. This concept is realized by a preprocessing module that can be utilized at the front-end of most mammographic CAD systems. Based on fractal encoding, this module takes a mammo-graphic image as its input and generates, as its output, a collection of subregions called focus-of-attention regions (FARs). These FARs contain all structures in the input image that appear to be different from the normal background tissue. Subsequently, the CAD systems need only to process the presented FARs, rather than the entire input image. This accomplishes two objectives simultaneously: (1) an increase in throughput via a reduction in the input data, and (2) a reduction in false detections by limiting the scope of the detection algorithms to FARs only. The pilot study consisted of using the preprocessing module to analyze 80 mammographic images. The results were an average data reduction of 83% over all 80 images and an average false detection reduction of 86%. Furthermore, out of a total of 507 marked microcalcifications, 467 fell within FW, representing a coverage rate of 92%.