The quantification of organ volumes from SPECT images suffers from two major problems: image segmentation and imperfect system transfer function. Image segmentation defines the borders of an organ and allows volume measurements by counting the voxels inside this contour in all slices containing parts of this organ. A review of the literature, showed that several investigators use a fixed threshold (FT) to determine the organ pixels. It is our aim to demonstrate that the threshold has to be adapted to every single case because its value is dependent upon several factors, such as size and contrast. Therefore a threshold selection algorithm, based on the gray level histogram (GLH), is evaluated. It is nearly impossible to calculate and eliminate errors induced by the complex system response function. A correction method based on linear regression is proposed. By minimizing the relative error (sigma), a linear correlation (Y = AX + B) between the true volume (Y) and the measured volume (X) is established for three fixed thresholds (30%, 40%, 50%) and for the GLH method. The methods are evaluated on a series of nineteen phantoms with a volume range between 9.8 and 202.5 ml. The relative error is minimal for the GLH method. The whole procedure is semi-automated and virtually operator independent.