Literature DB >> 23104971

Informatics in radiology: what can you see in a single glance and how might this guide visual search in medical images?

Trafton Drew1, Karla Evans, Melissa L-H Võ, Francine L Jacobson, Jeremy M Wolfe.   

Abstract

Diagnostic accuracy for radiologists is above that expected by chance when they are exposed to a chest radiograph for only one-fifth of a second, a period too brief for more than a single voluntary eye movement. How do radiologists glean information from a first glance at an image? It is thought that this expert impression of the gestalt of an image is related to the everyday, immediate visual understanding of the gist of a scene. Several high-speed mechanisms guide our search of complex images. Guidance by basic features (such as color) requires no learning, whereas guidance by complex scene properties is learned. It is probable that both hardwired guidance by basic features and learned guidance by scene structure become part of radiologists' expertise. Search in scenes may be best explained by a two-pathway model: Object recognition is performed via a selective pathway in which candidate targets must be individually selected for recognition. A second, nonselective pathway extracts information from global or statistical information without selecting specific objects. An appreciation of the role of nonselective processing may be particularly useful for understanding what separates novice from expert radiologists and could help establish new methods of physician training based on medical image perception. © RSNA, 2012.

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Year:  2012        PMID: 23104971      PMCID: PMC3545617          DOI: 10.1148/rg.331125023

Source DB:  PubMed          Journal:  Radiographics        ISSN: 0271-5333            Impact factor:   5.333


  50 in total

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5.  Perceptual skill, radiology expertise, and visual test performance with NINA and WALDO.

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6.  Templates in chess memory: a mechanism for recalling several boards.

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Journal:  Cogn Psychol       Date:  1996-08       Impact factor: 3.468

7.  Contextual cueing: implicit learning and memory of visual context guides spatial attention.

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Journal:  Proc Natl Acad Sci U S A       Date:  1998-02-03       Impact factor: 11.205

9.  Recognition of natural scenes from global properties: seeing the forest without representing the trees.

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Journal:  Cogn Psychol       Date:  2008-08-30       Impact factor: 3.468

10.  Processing scene context: fast categorization and object interference.

Authors:  Olivier R Joubert; Guillaume A Rousselet; Denis Fize; Michèle Fabre-Thorpe
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  45 in total

1.  Adaptation and visual search in mammographic images.

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2.  A collaborative computer aided diagnosis (C-CAD) system with eye-tracking, sparse attentional model, and deep learning.

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Review 3.  Essentials of forensic post-mortem MR imaging in adults.

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Review 4.  Application of contrast media in post-mortem imaging (CT and MRI).

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5.  Collaboration improves unspeeded search in the absence of precise target information.

Authors:  Alison Enright; Nathan Leggett; Jason S McCarley
Journal:  Atten Percept Psychophys       Date:  2020-10       Impact factor: 2.199

6.  Through the eyes of the expert: Evaluating holistic processing in architects through gaze-contingent viewing.

Authors:  Spencer Ivy; Taren Rohovit; Mark Lavelle; Lace Padilla; Jeanine Stefanucci; Dustin Stokes; Trafton Drew
Journal:  Psychon Bull Rev       Date:  2021-01-29

7.  The Radiologist's Gaze: Mapping Three-Dimensional Visual Search in Computed Tomography of the Abdomen and Pelvis.

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Journal:  J Digit Imaging       Date:  2019-04       Impact factor: 4.056

8.  Do clinicians decide relying primarily on Bayesians principles or on Gestalt perception? Some pearls and pitfalls of Gestalt perception in medicine.

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9.  Reading different literature helps one to learn to listen.

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Journal:  Intern Emerg Med       Date:  2014-05-31       Impact factor: 3.397

10.  An expert advantage in detecting unfamiliar visual signals in noise.

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Journal:  Proc Natl Acad Sci U S A       Date:  2020-09-30       Impact factor: 11.205

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