Four methods of brain edge detection on brain SPET perfusion (99Tcm-hexamethylpropylene amine oxime) images were compared: ellipse adaptation, simple thresholding (four threshold values), a low threshold (40%) followed by 1, 2 or 3 pixel erosion, and the Deriche 3D adaptive cut-off frequency method (four filter widths: alpha = 1, 2, 3 or 4). The SPET data of six patients were reconstructed to obtain 10 axial slices, each 10 mm thick, covering the whole brain. On the 60 axial slices, the methods were compared based on automaticity, computation time and accuracy of edge detection compared with morphological edges drawn manually on the patients' 3D co-registered magnetic resonance imaging (MRI) scans. The proportion of pixels inside the contour defined by the MRI scan but outside the SPET edge (p(i)), and the proportion of pixels inside the contour defined by the SPET image but outside the MRI contour (pe), were calculated. The thresholding methods provided interesting results, particularly the application of a low threshold value (40%), followed by a 2 pixel erosion, which required a computation time of 12 s (p(i) = 5.7 +/- 2.2%; pe = 2.7 +/- 0.9%). Because of adjustments to each slice of the ellipse axis, the processing time of this method was about 3 min (p(i) = 1.5 +/- 1.4%; pe = 11.3 +/- 3.4%). The Deriche 3D filter was time-consuming (6 min for 10 slices on a NXT workstation, SMV International). With this method, the best edge fitting was found with a filter width of 3 and 4 (p(i) = 9.6 +/- 11.1%; pe = 14.1 +/- 23.2%; alpha = 3). Three-dimensional filtering methods must be refined to reduce the computation time and to improve brain edge fitting accuracy when compared with the eroded thresholding method.