Title :
An automated vertebra identification and segmentation in CT images
Author :
Aslan, Melih S. ; Ali, Asem ; Rara, Ham ; Farag, Aly A.
Author_Institution :
Comput. Vision & Image Process. Lab., Univ. of Louisville, Louisville, KY, USA
Abstract :
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.
Keywords :
Gaussian processes; Markov processes; computerised tomography; graph theory; image segmentation; matched filters; medical image processing; CT images; Markov Gibbs random field; automated vertebra identification; clinical computed tomography images; cortical bones; graph cuts method; image segmentation; linear combination of Gaussians; local volume growing methods; matched filter; trabecular bones; Accuracy; Biomedical imaging; Bones; Computed tomography; Image segmentation; Spine; Three dimensional displays; Spine Bone; Vertebral Body (VB); graph cuts segmentation; trabecular bone;
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2010.5651959