Background. We describe a set of image processing algorithms and mathematical models that can be advantageously used in schemes for the segmentation of thallium-201-single photon emission computed tomography (SPECT) images and for computation of left ventricular ejection fraction (EF). Methods. The system consists of two independent blocs for image segmentation and computation of function. The former is based on a multiresolution elliptical coordinate transformation and dynamic contour tracking. Computation of EF is formulated on the basis of both the endocardial and epicardial contours, and we compare this formulation with that using only the endocardial border for images with low signal-to-noise ratios. The accuracy of border detection was validated against manual border tracing on FDG-PET images, simulated Tl-201-SPECT images where the true underlying borders were known, and actual Tl-201-SPECT images. Finally, we compared EFs computed for FDG-PET, technetium-99m-SPECT and Tl-201-SPECT with those obtained from planar gated blood pool imaging. Results. The automatically obtained results always were within the manual uncertainty range. Agreement between myocardial volumes from positron emission tomography and automatically obtained values from the simulated Tl-201-SPECT images was excellent (r = 0.95, n = 32). Agreement between EFs from planar gated blood pool imaging and the other image modalities was good (FDG-PET: y = 5.89 + 1.21x, r = 0.92, see = 6.24, n = 19, Tc-99m-SPECT: y = -3.86 + 1.06x, r = 0.88, see = 7.78, n = 9, Tl-201-SPECT: y = 17.8 + 0.81x, r = 0.77, see = 7.44, n = 26). For noisy input data the combined use of information from epicardial and endocardial contours gives more accurate EF values than the traditional formula on the basis of the endocardial contour only. Conclusions. Alternate approaches for segmentation and computation of function have been presented and validated. They might also be advantageously incorporated into other existing techniques.