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Proceedings Paper

Comparison of morphological and conventional edge detectors in medical imaging applications
Author(s): Lotfi Kaabi; Mansur Loloyan; H. K. Huang
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Paper Abstract

Recently, mathematical morphology has been used to develop efficient image analysis tools. This paper compares the performance of morphological and conventional edge detectors applied to radiological images. Two morphological edge detectors including the dilation residue found by subtracting the original signal from its dilation by a small structuring element, and the blur-minimization edge detector which is defined as the minimum of erosion and dilation residues of the blurred image version, are compared with the linear Laplacian and Sobel and the non-linear Robert edge detectors. Various structuring elements were used in this study: regular 2-dimensional, and 3-dimensional. We utilized two criterions for edge detector's performance classification: edge point connectivity and the sensitivity to the noise. CT/MR and chest radiograph images have been used as test data. Comparison results show that the blur-minimization edge detector, with a rolling ball-like structuring element outperforms other standard linear and nonlinear edge detectors. It is less noise sensitive, and performs the most closed contours.

Paper Details

Date Published: 1 June 1991
PDF: 13 pages
Proc. SPIE 1445, Medical Imaging V: Image Processing, (1 June 1991); doi: 10.1117/12.45198
Show Author Affiliations
Lotfi Kaabi, UCLA School of Medicine (United States)
Mansur Loloyan, UCLA School of Medicine (United States)
H. K. Huang, UCLA School of Medicine (United States)

Published in SPIE Proceedings Vol. 1445:
Medical Imaging V: Image Processing
Murray H. Loew, Editor(s)

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