HUMAN vs. VISION MODEL PERFORMANCE
FOR TWO MEDICAL IMAGE ESTIMATION TASKS

Derek Thomas Puff

	A computed method for measuring medical image quality would allow 
fast and economical evaluation of image acquisition and display systems 
without the need for arduous, expensive human observer experiments.  It would 
help such a method to be predictive of human assessment if it reflected the 
principles thought to govern the operation of the visual system.  This 
dissertation research implemented and tested the accuracy of a measure of 
medical image quality that incorporates a model of human vision in a 
simulation of human image interpretation.  It was hypothesized that the model, 
by performing in a way that reflected the inherent capabilities and 
limitations of a human, would be predictive of human performance as 
physical properties of the image varied.  The core model of shape perception, 
a theory for the representation of objects that may serve as a fundamental
 perceptual basis for a number of medical image interpretation tasks, was 
applied in computing estimates of the depth of a vessel stenosis in an 
angiogram and the position of a radiation treatment field relative to the 
spinal cord in a portal image.  Parameters of those imaging systems that 
have significant effects on the physical characteristics of the images, 
such as the amount of imaging system blur or the extent of contrast-enhancing 
processing, were systematically varied.  Model and human task performance 
was studied as a function of the parameters in order to assess the extent to 
which the model predicted the human results.  In most instances, the analysis 
suggested that the conformance of the model and human data was not sufficient 
to allow use of the visual model as proposed.  The conclusion explores the 
potential factors in those discrepancies and reiterates the claim that image 
quality assessments based upon fundamental principles of visual perception 
might eventually be utilized successfully for medical image interpretation
tasks.