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Generalized relative quality assessment scheme for reconstructed medical images

Issue title: Frontiers in Biomedical Engineering and Biotechnology – Proceedings of the 3rd International Conference on Biomedical Engineering and Biotechnology, 25–28 September 2014, Beijing, China

Article type: Research Article

Authors: Wang, Shaoze | Ding, Yong; | Dai, Hang | Qian, Dahong | Yu, Xinfeng | Zhang, Minming

Affiliations: Institute of VLSI Design, Zhejiang University, Hangzhou, Zhejiang 310027, China | Radiology Department, The Second Affiliated Hospital, Medical School of Zhejiang University, Hangzhou, Zhejiang 310027, China

Note: [] Corresponding author: Yong Ding, Institute of VLSI Design, Zhejiang University, Hangzhou, Zhejiang 310027, China. Tel.: +86 0571 87951071; Fax: +86 87942486; E-mail: [email protected].

Keywords: Relative quality, full reference, Bayesian inference, reconstructed image, subjective evaluation

DOI: 10.3233/BME-141105

Journal: Bio-Medical Materials and Engineering, vol. 24, no. 6, pp. 2865-2873, 2014

Published: 2014
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Abstract

A generalized relative quality (RQ) assessment scheme is proposed here based on the Bayesian inference theory, which is reasonable to make use of full reference (FR) algorithms when the evaluation of the quality of homogeneous medical images is required. Each FR algorithm is taken as a kernel to represent the level of quality. Although, various kernels generate different order of magnitude, a normalization process can rationalize the quality index within 0 and 1, where 1 represent the highest quality and 0 represents the lowest quality. To validate the performance of the proposed scheme, a series of reconstructed susceptibility weighted imaging images are collected, where each image has its subjective scale. Both experimental results and a ROC analysis show that the RQ obtained from the proposed scheme is consistent with subjective evaluation.

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