20 February 2012 Evaluation of HVS models in the application of medical image quality assessment
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In this study, four of the most widely used Human Visual System (HVS) models are applied on Magnetic Resonance (MR) images for signal detection task. Their performances are evaluated against gold standard derived from radiologists' majority decision. The task-based image quality assessment requires taking into account the human perception specificities, for which various HVS models have been proposed. However to our knowledge, no work was conducted to evaluate and compare the suitability of these models with respect to the assessment of medical image qualities. This pioneering study investigates the performances of different HVS models on medical images in terms of approximation to radiologist performance. We propose to score the performance of each HVS model using the AUC (Area Under the receiver operating characteristic Curve) and its variance estimate as the figure of merit. The radiologists' majority decision is used as gold standard so that the estimated AUC measures the distance between the HVS model and the radiologist perception. To calculate the variance estimate of AUC, we adopted the one-shot method that is independent of the HVS model's output range. The results of this study will help to provide arguments to the application of some HVS model on our future medical image quality assessment metric.
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L. Zhang, L. Zhang, C. Cavaro-Menard, C. Cavaro-Menard, P. Le Callet, P. Le Callet, } "Evaluation of HVS models in the application of medical image quality assessment", Proc. SPIE 8291, Human Vision and Electronic Imaging XVII, 82910T (20 February 2012); doi: 10.1117/12.905892; https://doi.org/10.1117/12.905892

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