The assessment of multiple sclerosis (MS) lesions would be a demanding and time-consuming task, because MS lesions present temporal changes in terms of shape, location and area. Therefore, the purpose of our study was to develop an automated method for detection of MS candidate regions in brain 3.0 Tesla two-dimensional magnetic resonance (MR) images. We applied a proposed method to 49 slices selected from 6 studies of three MS patients including 168 MS lesions. As a result, the sensitivity for detection of MS regions was 81.5 % with 2.9 false positives per slice based on a leave-one-candidate-out test.