Vertebral body segmentation of spine MR images using superpixels

Abstract

This paper presents a segmentation approach guided by the user for extracting the vertebral bodies of spine from MRI. The proposed approach, called VBSeg, takes advantage of superpixels to reduce the image complexity and then making easy the detection of each vertebral body contour. Superpixels adapt themselves to the image structures, once their formation law follows the homogeneity of the image regions. However, for some diseases or abnormalities, the boundary of each superpixel does not fit well in the vertebra contour. To avoid this drawback, we propose to use the Otsu’s method as a pos-segmentation step to divide the superpixels into smaller ones. The final segmentation is obtained through a region growing approach using points manually selected by the specialist. It can produce masks of the five lumbar vertebrae with an average precision of 80% and recall of 87%, when compared to the manual segmentation of a trained specialist. These values show that the VBSeg is a valuable asset to assist the medical specialist in the task of vertebral bodies’ segmentation, with much less effort and time demand.