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Current Medical Imaging

Editor-in-Chief

ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

Research Article

An Edge Preservation Index for Evaluating Nonlinear Spatial Restoration in MR Images

Author(s): Justin Joseph, Sivaraman Jayaraman, Rajadurai Periyasamy and Simi V. Renuka

Volume 13, Issue 1, 2017

Page: [58 - 65] Pages: 8

DOI: 10.2174/1573405612666160609131149

Price: $65

Abstract

Background: Edge preserving filters are widely preferred for medical image denoising as they do not degrade the morphological edges during smoothing. Even though, the operational parameters of these filters have crucial influence on their performance, the parameters are selected subjectively. The optimum values of the operational parameters can be selected objectively with the help of edge quality indices. The available edge quality indices either do not comply with the subjective quality ratings or they are prone to noise level.

Objectives: (a) To formulate an edge preservation metric which has good correlation with subjective fidelity ratings and is robust to noise (b) To demonstrate an objective method for the selection of optimum values of the operational parameters of the non-linear spatial filters using the newly formulated edge preservation metric.

Methods: Pratt’s Figure of Merit (PFOM) between the binary edge maps of the original and restored images, extracted via gradient based threshold, is used as the measure of extent to which edges are preserved during restoration. Magnetic Resonance (MR) images filtered by anisotropic diffusion for different values of number of iterations are used as ground truth images. The PFOM is compared with existing edge quality indices in terms of robustness to noise and correlation with subjective fidelity ratings.

Results: PFOM exhibits a correlation of 0.9998 with the subjective edge quality rating which is only 0.9802 for Edge Preservation Index (EPI).

Conclusion: The proposed index is robust to noise level and useful for optimizing the performance of non-linear spatial filters.

Keywords: Edge preservation index, Edge quality index, Image quality analysis, Pratt’s figure of merit, non-linear restoration.

Graphical Abstract

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