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      What can an echocardiographer see in briefly presented stimuli? Perceptual expertise in dynamic search

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          Abstract

          Background

          Experts in medical image perception are able to detect abnormalities rapidly from medical images. This ability is likely due to enhanced pattern recognition on a global scale. However, the bulk of research in this domain has focused on static rather than dynamic images, so it remains unclear what level of information that can be extracted from these displays. This study was designed to examine the visual capabilities of echocardiographers—practitioners who provide information regarding cardiac integrity and functionality. In three experiments, echocardiographers and naïve participants completed an abnormality detection task that comprised movies presented on a range of durations, where half were abnormal. This was followed by an abnormality categorization task.

          Results

          Across all durations, the results showed that performance was high for detection, but less so for categorization, indicating that categorization was a more challenging task. Not surprisingly, echocardiographers outperformed naïve participants.

          Conclusions

          Together, this suggests that echocardiographers have a finely tuned capability for cardiac dysfunction, and a great deal of visual information can be extracted during a global assessment, within a brief glance. No relationship was evident between experience and performance which suggests that other factors such as individual differences need to be considered for future studies.

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          Most cited references49

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          Bayes Factors

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            Visual search in scenes involves selective and nonselective pathways.

            How does one find objects in scenes? For decades, visual search models have been built on experiments in which observers search for targets, presented among distractor items, isolated and randomly arranged on blank backgrounds. Are these models relevant to search in continuous scenes? This article argues that the mechanisms that govern artificial, laboratory search tasks do play a role in visual search in scenes. However, scene-based information is used to guide search in ways that had no place in earlier models. Search in scenes might be best explained by a dual-path model: a 'selective' path in which candidate objects must be individually selected for recognition and a 'nonselective' path in which information can be extracted from global and/or statistical information. Copyright © 2010 Elsevier Ltd. All rights reserved.
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              Recognition of natural scenes from global properties: seeing the forest without representing the trees.

              Human observers are able to rapidly and accurately categorize natural scenes, but the representation mediating this feat is still unknown. Here we propose a framework of rapid scene categorization that does not segment a scene into objects and instead uses a vocabulary of global, ecological properties that describe spatial and functional aspects of scene space (such as navigability or mean depth). In Experiment 1, we obtained ground truth rankings on global properties for use in Experiments 2-4. To what extent do human observers use global property information when rapidly categorizing natural scenes? In Experiment 2, we found that global property resemblance was a strong predictor of both false alarm rates and reaction times in a rapid scene categorization experiment. To what extent is global property information alone a sufficient predictor of rapid natural scene categorization? In Experiment 3, we found that the performance of a classifier representing only these properties is indistinguishable from human performance in a rapid scene categorization task in terms of both accuracy and false alarms. To what extent is this high predictability unique to a global property representation? In Experiment 4, we compared two models that represent scene object information to human categorization performance and found that these models had lower fidelity at representing the patterns of performance than the global property model. These results provide support for the hypothesis that rapid categorization of natural scenes may not be mediated primarily though objects and parts, but also through global properties of structure and affordance.
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                Author and article information

                Contributors
                ann.carrigan@mq.edu.au
                Journal
                Cogn Res Princ Implic
                Cogn Res Princ Implic
                Cognitive Research: Principles and Implications
                Springer International Publishing (Cham )
                2365-7464
                21 July 2020
                21 July 2020
                December 2020
                : 5
                : 30
                Affiliations
                [1 ]GRID grid.1004.5, ISNI 0000 0001 2158 5405, Centre for Elite Performance, Expertise and Training, , Macquarie University, ; North Ryde, Australia
                [2 ]GRID grid.1004.5, ISNI 0000 0001 2158 5405, Perception in Action Research Centre, , Macquarie University, ; Blacktown, Australia
                [3 ]GRID grid.1004.5, ISNI 0000 0001 2158 5405, Department of Psychology, , Macquarie University, ; 4 First Walk, North Ryde, NSW 2109 Australia
                [4 ]GRID grid.1029.a, ISNI 0000 0000 9939 5719, School of Medicine, , Western Sydney University, ; Blacktown, Australia
                [5 ]Westmead Private Cardiology, Westmead, Australia
                [6 ]GRID grid.460687.b, ISNI 0000 0004 0572 7882, Blacktown Mount Druitt Hospital, ; Sydney, Australia
                Author information
                http://orcid.org/0000-0002-2525-9241
                Article
                232
                10.1186/s41235-020-00232-7
                7374494
                32696181
                428c34ef-f209-4689-be7b-0310211e3bbd
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 December 2019
                : 26 May 2020
                Funding
                Funded by: Australian Research Council
                Award ID: DP180100425
                Funded by: Centre for Elite Performance, Expertise and Training
                Award ID: NA
                Categories
                Original Article
                Custom metadata
                © The Author(s) 2020

                echocardiography,vision,perception,expertise
                echocardiography, vision, perception, expertise

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