Literature DB >> 18572124

Using gaze-tracking data and mixture distribution analysis to support a holistic model for the detection of cancers on mammograms.

Harold L Kundel1, Calvin F Nodine, Elizabeth A Krupinski, Claudia Mello-Thoms.   

Abstract

RATIONALE AND
OBJECTIVES: Use data collected independently at three institutions to compare time to first fixate the true lesion in searching for cancers on mammograms. Examine the fit of the results to a holistic model of visual perception.
MATERIALS AND METHODS: The time required to first fixate a cancer on a mammogram was extracted from 400 eye-tracking records collected independently from three institutions. The time was used as an indicator of the initial perception of cancer. The distribution of first fixation times was partitioned into two normally distributed components using mixture distribution analysis. The true-positive fraction of each component was calculated.
RESULTS: About 57% of the cancers had a 95% chance of being fixated in the first second of viewing. The remainder took longer (range, 1.0 to 15.2 seconds). The true-positive fraction was larger for the lesions hit immediately for most of the readers (TPF = 0.63 vs. 0.52, F = 5.88, P = .02) in 68% (13/19) of the readers.
CONCLUSIONS: The initial detection occurs before visual scanning and, therefore, must be the result of a parallel "global" analysis of the image resulting in an initial holistic, gestalt-like perception. The development of expertise in medical image analysis may consist of a shift in the recognition mechanism from scan-look-detect to look-detect-scan.

Entities:  

Mesh:

Year:  2008        PMID: 18572124     DOI: 10.1016/j.acra.2008.01.023

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  32 in total

1.  Accuracy is in the eyes of the pathologist: The visual interpretive process and diagnostic accuracy with digital whole slide images.

Authors:  Tad T Brunyé; Ezgi Mercan; Donald L Weaver; Joann G Elmore
Journal:  J Biomed Inform       Date:  2017-01-10       Impact factor: 6.317

2.  Adaptation and visual search in mammographic images.

Authors:  Elysse Kompaniez-Dunigan; Craig K Abbey; John M Boone; Michael A Webster
Journal:  Atten Percept Psychophys       Date:  2015-05       Impact factor: 2.199

3.  The Medical Image Perception Society update on key issues for image perception research.

Authors:  Elizabeth A Krupinski; Kevin S Berbaum
Journal:  Radiology       Date:  2009-08-25       Impact factor: 11.105

4.  Optimizing the interpretation of capsule endoscopic images: shortsighted or taking the long view?

Authors:  Anastasios Koulaouzidis; Ervin Toth
Journal:  Dig Dis Sci       Date:  2015-02-28       Impact factor: 3.199

5.  Overwhelmed by choices.

Authors:  M Castillo
Journal:  AJNR Am J Neuroradiol       Date:  2012-08-23       Impact factor: 3.825

6.  Dog owners show experience-based viewing behaviour in judging dog face approachability.

Authors:  Carla Jade Gavin; Sarah Houghton; Kun Guo
Journal:  Psychol Res       Date:  2015-10-20

Review 7.  Review of prospects and challenges of eye tracking in volumetric imaging.

Authors:  Antje C Venjakob; Claudia R Mello-Thoms
Journal:  J Med Imaging (Bellingham)       Date:  2015-09-29

8.  An eye tracking study of bloodstain pattern analysts during pattern classification.

Authors:  R M Arthur; J Hoogenboom; R D Green; M C Taylor; K G de Bruin
Journal:  Int J Legal Med       Date:  2017-10-18       Impact factor: 2.686

Review 9.  HOW DO RADIOLOGISTS USE THE HUMAN SEARCH ENGINE?

Authors:  Jeremy M Wolfe; Karla K Evans; Trafton Drew; Avigael Aizenman; Emilie Josephs
Journal:  Radiat Prot Dosimetry       Date:  2015-12-08       Impact factor: 0.972

10.  Application of threshold-bias independent analysis to eye-tracking and FROC data.

Authors:  Dev P Chakraborty; Hong-Jun Yoon; Claudia Mello-Thoms
Journal:  Acad Radiol       Date:  2012-10-04       Impact factor: 3.173

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