EM algorithm based intervertebral disc segmentation on MR images

Abstract

Image segmentation is well known in partitioning a digital image into several segments. Recent days lower back pain in human being increases and so the lumber spine pathology detection becomes a predominant research area in Computer Aided Diagnosis (CAD) system. In the process of lumbar spine pathology detection, the segmentation of the Intervertebral Disc (IVD) is the major step as it identifies the IVDs or the boundaries of the IVDs either normal or abnormal in images. When the axial or the sagittal View of lumbar spine MR image is given as input, this proposed work segments the IVD in both the axial and sagittal views. The segmentation of IVD is a four stage process. First, Expectation-Maximization (EM) segmentation is performed on the MR Image. EM segmentation yields an advantage over K-means with the case of the size of clustering. The second stage is to carry out the morphological operators and third, apply edge detection method and obtain the edges. The final stage is to remove unwanted objects from the obtained output image. If this proposed segmentation is utilized as part of the CAD, the experts will be benefited for localizing the IVD and to diagnose the IVD disease.