We developed a novel clinical tool (PERFIT) for automated 3-D voxel-based quantification of myocardial perfusion, validated it with a wide spectrum of angiographically correlated cases, compared it to previous approaches, and tested its agreement with visual expert reading. A multistage, 3-D iterative inter- subject registration of patient images to normal stress and rest cardiac templates was applied, including automated masking of external activity before final fit. The reference templates were adjusted to the individual left ventricles by template erosion, for further shape correction. 125 angiographically correlated cases including multi-vessel disease, infarction, and dilated ventricles were tested. In addition, standard polar maps were generated automatically from the registered data. Results of consensus visual reading (V) and PERFIT (P) were compared. The iterative fitting was successful in 245/250 (99%) stress and rest images. PERFIT found defects on stress in 2/29 normal patients and 95/96 abnormal patients. Overall correlation between V and P findings was r equals 0.864. In all abnormal groups (n equals 96), PERFIT average defect sizes expressed as the percentage the myocardial volume were 9.6% for rest and 22.3% for stress, versus 11.4% (rest) and 23% (stress) for visual reading. Automatic quantification by PERFIT is consistent with visual analysis; it can be applied to the analysis whole spectrum of clinical images, and can aid physicians in interpretation of myocardial perfusion.