Document Detail


Salience measure for assessing scale-based features in mammograms.
MedLine Citation:
PMID:  18059917     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
Philip Perconti; Murray H Loew
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of the Optical Society of America. A, Optics, image science, and vision     Volume:  24     ISSN:  1084-7529     ISO Abbreviation:  J Opt Soc Am A Opt Image Sci Vis     Publication Date:  2007 Dec 
Date Detail:
Created Date:  2007-12-06     Completed Date:  2008-04-11     Revised Date:  2008-11-21    
Medline Journal Info:
Nlm Unique ID:  9800943     Medline TA:  J Opt Soc Am A Opt Image Sci Vis     Country:  United States    
Other Details:
Languages:  eng     Pagination:  B81-90     Citation Subset:  IM    
Affiliation:
US Army, Night Vision and Electronic Sensors Directorate, Fort Belvoir, Virginia 22060, USA. philip.perconti@us.army.mil
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MeSH Terms
Descriptor/Qualifier:
Analysis of Variance
Cues*
Decision Theory
Differential Threshold
Humans
Linear Models
Mammography / methods*,  statistics & numerical data
Observer Variation
Reference Values
Signal Detection, Psychological*
Subtraction Technique
Task Performance and Analysis
Visual Perception*
Weights and Measures*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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