An automated vertebra identification and segmentation in CT images

In this paper, we propose a new 3D framework to identify and segment VBs and TBs in clinical computed tomography (CT) images without any user intervention. The Matched filter is employed to detect the VB region automatically on axial axis. To identify the VB on coronal and sagittal axis, we use a new developed approach based on 4 points automatically placed on cortical shell. To segment the identified VB, the graph cuts method which integrates a linear combination of Gaussians (LCG) and Markov Gibbs Random Field (MGRF) are used. Then, the cortical and trabecular bones are segmented using local volume growing methods. Experiments on the data sets show that the proposed segmentation approach is more accurate than other known alternatives.

• Type: Journal
• Year: 2010
• Where: ICIP
• Authors: Melih S. Aslan, Asem M. Ali, Ham Rara, Aly A. Farag
• Keywords: Clinical Computed Tomography, Gibbs Random Field, ICIP 2010, Image Processing, Volume Growing Methods