A 3-DIMENSIONAL 2ND-DERIVATIVE SURFACE-DETECTION ALGORITHM FOR VOLUMEDETERMINATION ON SPECT IMAGES

Most existing techniques for determining volumes on single-photon-emis sion computed tomography (SPECT) data employ thresholding, two-dimensi onal edge detection, or manual delineation of edges. These methods, ho wever, are limited in both accuracy and applicability. In seeking to o vercome these limitations, a truly three-dimensional (3D) second-deriv ative-based algorithm which can be implemented with relative ease has been developed. The method incorporates 3D matrix operators; these are convoluted with the SPECT count data in order to produce a 3D Voxel m ap whose data elements correspond to the second derivative of counts i n the image. This map is then searched, a suitable derivative-based ed ge-defining criterion being applied to each voxel position, in order t o locate the derivative surface boundary which defines the volume. Val idation is obtained using phantom data from Tc-99m-filled bottles of v olumes 200, 580 and 2500 cm3 placed within a body-sized tank containin g background activities set to give a range of contrasts between 1.00 and 0.75 (i.e. background 0% to 25%). The performance of the algorithm is encouraging: the volumes of the two larger bottles are determined to within a 3% accuracy without the need for any prior calibration, an d the results obtained over all bottle sizes are found to be contrast independent to within approximately 4%.