Deformable Fourier surfaces for volume segmentation in SPECT

Three-dimensional boundary finding based on Fourier surface optimization is presented as a method for segmentation of SPECT images. Being robust against noise and adjustable with respect to its detail resolution, it forms an interesting alternative in this application area. A three-dimensional approach can also be assumed to increase the possibility of delineating low contrast regions, as compared to a two-dimensional slice-by-slice approach. We apply boundary finding to Monte Carlo simulated SPECT images of the computer-based anthropomorphic Zubal phantom in order to evaluate the influence of object contrast and noise on the segmentation accuracy. Segmentation is also performed in real patient images.