Literature DB >> 18059917

Salience measure for assessing scale-based features in mammograms.

Philip Perconti1, Murray H Loew.   

Abstract

This work assesses the usefulness of an objective, task-based image quality measure that is correlated with perceived image quality; the measure uses the most salient features contained within a medical image. Contributions include the development of a perceptually correlated metric that is useful for quantifying the salience of local, low-level visual cues and identifying those spatial frequencies that are most distinct and perhaps most relied upon by radiologists for decision making. A set of 40 mammograms and registered eye position data from nine observers was used to evaluate the salience metric. A parsimonious analysis-of-variance model explained the variance in the salience results. This analysis is generalized to a population of readers and cases. An analysis of salience versus time of first eye fixation shows good correlation with true positive lesions that were found by experienced readers in less than 2 s.

Mesh:

Year:  2007        PMID: 18059917     DOI: 10.1364/josaa.24.000b81

Source DB:  PubMed          Journal:  J Opt Soc Am A Opt Image Sci Vis        ISSN: 1084-7529            Impact factor:   2.129


  1 in total

1.  Application of unsupervised learning to hyperspectral imaging of cardiac ablation lesions.

Authors:  Shuyue Guan; Huda Asfour; Narine Sarvazyan; Murray Loew
Journal:  J Med Imaging (Bellingham)       Date:  2018-12-15
  1 in total

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