
Proceedings Paper
Peripheral nerve enhancement based on multi-scale Hessian matrixFormat | Member Price | Non-Member Price |
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Paper Abstract
To improve the precision of nerve segmentation in CT images, a new comparability function is proposed in this paper
to enhance the contrast between nerve structure and other surrounding tissues. It is based on nerve's characteristic, i.e.
dark tubular structure, and a thorough analysis of the multi-scale Hessian matrix. By comparability function, the gray
range of interested nerve structure can be automatically determined, which combines the multi-scale Hessian matrix
eigenvalues with intensity information of original nerve CT images. The experimental results show that the improved
algorithm can not only enhance the continuous nerve of tubular structure, but also clearly reflect its bifurcations and
crossovers. It is very important and significant to the computer-aided disease diagnosis of peripheral nervous system.
Paper Details
Date Published: 8 July 2011
PDF: 5 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80091N (8 July 2011); doi: 10.1117/12.896498
Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)
PDF: 5 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80091N (8 July 2011); doi: 10.1117/12.896498
Show Author Affiliations
Xiuli Ma, Shanghai Univ. (China)
Hui Li, Shanghai Univ. (China)
Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)
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