DocumentCode :
2500363
Title :
Intensity ridge and widths for tubular object segmentation and description
Author :
Aylward, Stephen ; Bullitt, Elizabeth ; Pizer, Stephen ; Eberly, David
Author_Institution :
Dept. of Comput. Sci., North Carolina Univ., Chapel Hill, NC, USA
fYear :
1996
fDate :
21-22 Jun 1996
Firstpage :
131
Lastpage :
138
Abstract :
Introduces a technique for the automated description of tubular objects in 3D medical images. The goal of automated 3D object description is to extract a representation which consistently details the location, size, and structure of objects in 3D images using minimal user interaction. Such a representation provides a means by which objects can be classified, quantifiably evaluated, and registered. It also serves as a region of interest specification for visualization processes. The technique presented in this paper is suited for generating representations of 3D objects with nearly circular cross sections which have, possibly as a result of a global operation (e.g., blurring), intensity extrema near their centers. Such tubular objects commonly occur within human anatomy (e.g., vessels and selected bones). The medial axis of each of these objects is well approximated by its intensity ridge. The scales of the local maxima in medialness at all points along the ridge can be mapped to local width estimates. Together these measures capture the location, size, and structure of tubular objects. This paper covers the mathematical basis, the implementation issues, and the application of this technique to the extraction of vessels from 3D magnetic resonance angiographic images and bones from 3D X-ray computed tomographic images
Keywords :
biomedical NMR; bone; computerised tomography; feature extraction; image segmentation; medical image processing; 3D X-ray computed tomographic images; 3D magnetic resonance angiographic images; 3D medical images; automated description; blurring; bones extraction; global operation; human anatomy; intensity extrema; intensity ridge; medial axis; medical diagnostic imaging; nearly circular cross sections; tubular object segmentation; vessels extraction; Biomedical imaging; Bones; Computed tomography; Filters; Image analysis; Magnetic resonance; Magnetic resonance imaging; Object segmentation; Visualization; X-ray imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mathematical Methods in Biomedical Image Analysis, 1996., Proceedings of the Workshop on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-8186-7368-0
Type :
conf
DOI :
10.1109/MMBIA.1996.534065
Filename :
534065
Link To Document :
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