In MR imaging, image noise, bias field, and partial volume effect are adverse phenomena that increases intertissue overlapping and hampers quantitative analysis. This study provides a powerful fully automated classification method, which combines the bias field correction and PV segmentation together. The method has been validated on simulated and real MR images for which gold standard segmentation available. The experimental results show that the proposed method is more accurate and robust than currently available models.