Methods Inf Med 2000; 39(01): 1-6
DOI: 10.1055/s-0038-1634262
Original Article
Schattauer GmbH

Statistical Support for Uncertainty in Radiological Diagnosis

D. Teather
1   Department of Medical Statistics, De Montfort University, Leicester
,
B. A. Teather
1   Department of Medical Statistics, De Montfort University, Leicester
,
N. P. Jeffery
1   Department of Medical Statistics, De Montfort University, Leicester
,
G. H. du Boulay
1   Department of Medical Statistics, De Montfort University, Leicester
2   Institute of Neurology, London
,
B. du Boulay
3   School of Cognitive and Computing Sciences, University of Sussex, UK
,
M. Sharples
4   School of Electronic and Electrical Engineering, University of Birmingham, UK
› Institutsangaben
Weitere Informationen

Publikationsverlauf

Publikationsdatum:
07. Februar 2018 (online)

Abstract:

Radiological interpretation and diagnosis involves the comparison and classification of complex medical images and is typical of the categorisation tasks that have been the subject of observational studies in Cognitive Science. This paper considers the affinity between statistical modelling and theories of categorisation for naturally occurring categories. Statistical based measures of similarity and typicality with a probabilistic interpretation are derived. The utilisation of these measures in the support of diagnosis under uncertainty via interactive overview plots is described. The application of the methodology to magnetic resonance imaging of the head is considered. The methods detailed have application to other fields involving archiving and retrieving of image data.

 
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