DocumentCode :
2574238
Title :
A novel spinal vertebrae segmentation framework combining geometric flow and shape prior with level set method
Author :
Lim, Poay Hoon ; Bagci, Ulas ; Aras, Omer ; Wang, Yan ; Bai, Li
Author_Institution :
Sch. of Comput. Sci., Univ. of Nottingham, Nottingham, UK
fYear :
2012
fDate :
2-5 May 2012
Firstpage :
1703
Lastpage :
1706
Abstract :
Segmentation of spinal vertebrae is extremely important in the study of spinal related disease or disorders. However, limited work has been done on precise segmentation of spinal vertebrae. The complexity of vertebrae shapes, with gaps in the cortical bone, internal boundaries, as well as the noisy, incomplete or missing information from the images have undoubtedly increased the challenge for image analysis. In this paper, we introduce a novel level set segmentation framework that integrates shape prior and the Willmore flow to drive the level set evolution. While the shape energy draws the level set function towards a range of possible prior shapes, the edge-mounted Willmore energy captures the localized geometry information and smooths the surface during the level set evolution. Experimental results on segmentation of spinal vertebrae from CT images demonstrate the powerful combination of prior knowledge and geometrical flow.
Keywords :
bone; computerised tomography; diseases; image segmentation; medical disorders; medical image processing; neurophysiology; CT images; cortical bone; edge-mounted Willmore flow energy; image analysis; internal boundaries; level set evolution method; localized geometry information; novel spinal vertebrae segmentation framework; spinal related disease; spinal related disorders; Estimation; Image edge detection; Image segmentation; Kernel; Level set; Mathematical model; Shape; Vertebrae segmentation; Willmore flow; computed tomography; kernel density estimation; level set method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on
Conference_Location :
Barcelona
ISSN :
1945-7928
Print_ISBN :
978-1-4577-1857-1
Type :
conf
DOI :
10.1109/ISBI.2012.6235907
Filename :
6235907
Link To Document :
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