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Magnetic resonance imaging has revolutionized the detection of small structural abnormalities in patients with epilepsy. However, many focal abnormalities remain undetected in routine radiological inspection. We introduce a quantitative method using morphometric features related to epileptogenic cortical malformations to detect aberrant cortical thickness and blurred gray-white matter boundaries. Using MRI morphometry at 3T with surface-based spherical averaging techniques that precisely align anatomical structures between individual brains, we compared single patients with known lesions to a large normal control group to detect clusters of abnormal cortical thickness and gray-white matter contrast (GWC). To assess the effects of threshold and smoothing on detection sensitivity and specificity, we systematically varied these parameters with 13 different thresholds and 3 smoothing levels. Structural abnormalities detected by this method were compared to intracranial EEG, pathological cell markers using post-resection histology and surgical outcome. With optimal parameters and by combining thickness and GWC, the surface-based detection method identified 92% of cortical lesions (sensitivity) with few false positives (96% specificity), successfully discriminating patients from controls 94% of the time. The detected structural abnormalities were related to the seizure onset zones, abnormal histology and positive outcome in all surgical patients. This automated approach may be a valuable clinical tool to detect previously occult malformations and improve identification of patients with intractable focal epilepsy that may benefit from surgery.