Absorption Systems In Radio-Selected QSO Surveys

Radio-selected samples of quasars with complete optical identifications offer an ideal dataset with which to investigate dust bias associated with intervening absorption systems. Here, we review our work on the Complete Optical and Radio Absorption Line System (CORALS) survey whose aim is to quantify this bias and assess the impact of dust on absorber statistics. First, we review previously published results on the number density and gas content of high column density absorbers over the redshift range 0.6 < z < 3.5. We then present the latest results from CORALS which focus on measuring the metal content of our unbiased absorber sample and an investigation of their optical--IR colours. Overall we find that although dust is unarguably present in absorption galaxies, the level appears to be low enough that the statistics of previous magnitude limited samples have not been severely affected and that the subsequent reddening of background QSOs is small.Comment: Proceedings of IAUC199, Probing Galaxies through Quasar Absorption Lines, P. R. Williams, C. Shu, and B. Menard, ed

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

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

International audienc

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

Novel robotic assistive technologies: choosing appropriate training for healthcare professionals

One of the key challenges for the training of healthcare professionals (HCPs) is to maintain a good understanding and knowledge of new assistive technologies (ATs) that are currently on the market [1]. Indeed, at present, available training on ATs is limited and does not meet the practice-related needs of HCPs. It is in this context that the ADAPT European project aims to develop a new AT training programme for healthcare professionals, which will also introduce them to the project’s new AT developments - a smart powered wheelchair and a virtual reality wheelchair-driving simulator. The program consists of six multimodal units; five delivered via e-learning and one through a blended method of e-learning and face-to-face sessions. The development of the content is guided by findings from an earlier literature review and an online survey of AT training needs for HCP’s, both undertaken by the ADAPT cross-national research team, comprised of UK and French experts. The level of technical difficulty increases with successive units in order to train all HCPs to use innovative ATs more widely in their practice. A Learning Management System enables the dissemination of the e-learning AT program. Preliminary results from participant unit-specific evaluations available at this stage are overall positive and encouraging