Robust Edge Detection Applied to Multi-Parametric Magnetic Resonance Images
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Date
2016-11
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Addis Ababa University
Abstract
Various edge detection techniques for color images that have been proposed in the last two decades showed that color images contain 10% additional edge information as compared to their gray scale counterparts. Edge detection is one of the most commonly used operations in medical color image processing. Efficient and accurate edge detection leads to increased performance of subsequent image processing techniques, including image segmentation, object-based image coding, and image retrieval. A color image edge detection algorithm is proposed in this paper that introduces a robust and automated scheme that makes use of higher order statistical features derived from locally computed trinion Fourier transforms. The proposed scheme uses a holistic vectorial representation of the color images in the three (trinion) space and applies trinion based Fourier transforms to extract useful imaging features for the purpose of edge detection of multi parametric magnetic resonance images (MP-MRI). A suitable color space transformation and a way of extracting robust higher order features are included in the method. Performance of the proposed scheme is compared against classical edge detection methods and other vectorial approaches which have been proposed in the literature. Results have shown that none of the classical as well as the other vectorial approaches were able to detect useful edges. Application of the method is shown in edge detection on MP-MR images of brain scans of patients treated for Glioblastoma multiforme (GBM). The algorithm performs well in detecting the tumor edges, that was (qualitatively) in a very good agreement with the ground truth information which is the oncologist‘s contour drawn manually. Key Words: Color Image processing, Edge detection, Trinion, Quaternion, Magnetic Resonance Image.
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Keywords
Color Image processing; Edge detection; Trinion; Quaternion; Magnetic Resonance Image