Statistical support for uncertainty in radiological diagnosis

Radiological interpretation and diagnosis involves the comparison and class ification of complex medical images and is typical of the categorisation ta sks that have been the subject of observational studies in Cognitive Scienc e. This paper considers the affinity between statistical modelling and theo ries of categorisation for naturally occurring categories. Statistical base d 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 applica tion of the methodology to magnetic resonance imaging of the head is consid ered. The methods detailed have application to other fields involving archi ving and retrieving of image data.