Using AUC to study perceptual difference model suitability for the detection task on MR image

International audienceSince the ultimate goal of medical images is to help radiologists to gain a high diagnostic accuracy, evaluating the medical image quality from the radiologists' perspective is a useful alternative compared to optimal observer approach. While several existing perceptual difference models are adopted toward this end, few works were conducted to evaluate the suitability of the models w.r.t. the diagnostic task performance. This study is trying to address this problem

Using eye-tracking to study diagnostic process during MRI scanning

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Diagnostic quality assessment of medical images: Challenges and trends

With medical imaging technologies growth, the question of their assessment on the impact and benefit on patient care is rising. Development and design of those medical imaging technologies should take into account the concept of image quality as it might impact the ability of practicians while they are using image information. Towards that goal, one should consider several human factors involved in image analysis and interpretation, e.g. image perception issues, decision process, image analysis pipeline (detection, localization, characterization...). While many efforts have been dedicated to objectively assess the value of imaging system in terms of ideal decision process, new trends have recently emerged to deal with human observer perfomances. This task effort is huge considering the variability of imaging acquisition methods and the possible pathologies. This paper proposes a survey of some key issues and results associated to this effort. We first outline the wide range of medical images with their own specific features. Next, we review the main methodologies to evaluate diagnostic quality of medical images from subjective assessment including ROC analysis, and diagnostic criteria quality analysis, to objective assessment including metrics based on the HVS, and model observers. At last, we present another evaluation method: eye-tracking studies to gain basic understanding of the visual search and decision-making process

QoE for Telemedicine: Challenges and Trends

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Evaluation of HVS models in the application of medical quality assessment

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\u27 decisions. The task-based image quality assessment requires taking into account the human perception specificities, for which various HVS models have been proposed. Few works were conducted however to evaluate and compare the suitability of these models with respect to the assessment of medical image qualities. Here we propose to score the performance of each HVS model using the AUC and its variance estimates as the figure of merit. The contribution of this work is twofold: firstly the application of MRMC (multiple-reader, multiple-case) estimates independently of the HVS model\u27s output range, secondly the use of radiologists\u27 consensus as gold standard so that the estimated AUC measures the distance between the HVS model and the radiologist perception

Color perception model. Application to image quality assessment

The design of image visual quality objective criteria is very useful in order to optimize the performances of image processing systems for storage and transmission of visual data. An objective quality criterion should provide quality measures in good correspondence with human judgment. So, it is necessary to introduce the main properties of the human visual system (HSV) in the design of such a criterion. This paper presents a very elaborated model of color images perception by the HVS. It takes into account and models in a coherent way the key functions of human perception : visual space for color representation, contrast sensitivity functions for achromatic and chromatic components respectively, perceptual channels decomposition, intra and inter pathways masking functions. All these models have been deduced from the interpretation of results of psychophysics experiments. Next, we present an application of the perception model to the design of an objective quality criterion with full reference for color images. This application is based on a critical analysis of different ways to construct the pooling function of perceived errors including inter-pathway pooling, inter-channel pooling and spatial pooling. The entire objective quality criterion have been tested on a database of natural color images which have been stressed with distortions of different nature and strength. Performances in terms of correlation with mean human judgment is more than 0.94 and 97 % of images are correctly assessed according to the accuracy on the subjective rate given by observers.La conception de critères objectifs d'évaluation de qualité visuelle des images est d'une grande utilité afin d'optimiser les performances des systèmes de traitement d'images pour le stockage et la transmission de l'information visuelle. Un critère objectif de qualité doit fournir des mesures de qualité en forte correspondance avec le jugement humain. Il est donc nécessaire d'intégrer des modèles des principales propriétés du système visuel humain dans la conception d'un tel critère. Ce papier présente un modèle très élaboré de perception des images couleur par le système visuel humain (SVH). Il prend en compte et modélise de façon cohérente les fonctions clé de la perception : espace de représentation visuelle des couleurs, fonctions de sensibilité aux contrastes des composantes achromatique et chromatiques, décomposition en canaux perceptifs, fonctions de masquage intra et inter composante. Tous ces modèles ont été déduits à partir de résultats de tests psychophysiques et de leur interprétation. L'application du modèle de perception à la conception d'un critère objectif de qualité d'images couleur avec image de référence est ensuite effectuée. Elle se base sur une analyse critique des différentes façons de construire une fonction de cumul des dégradations perçues : cumul inter-composante, cumul inter-canal, cumul spatial. L'ensemble du critère objectif de qualité a été testé sur une base d'images naturelles couleur ayant subies des dégradations de nature et de force différentes. Les performances en terme de corrélation avec le jugement humain moyen est supérieure à 0,94 et 97 % des images sont correctement évaluées au regard de la précision sur les notes subjectives données par l'humain

A MULTI-SLICE MODEL OBSERVER FOR MEDICAL IMAGE QUALITY ASSESSMENT

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Development of Partial Least Square models for the prediction of the concentration of a gustative stimulus in water from physiological data

International audienceClassical physicochemical or sensory methodologies are often inadequate to describe the perception of water and their correlation is complicated. Indeed, the taste of water is difficult to describe due to low concentrations of sapid molecules. The aim of this work was to combine sensory and physiological measurements in order to correlate data with chemical properties of sapid solutions