A novel objective quality assurance system for smear slide screening is
investigated in this thesis. A method of data validation was developed that
compares data from an eye tracked image display, machine image colour texture
analysis and expert judgements in a statistical manner to identify salient areas of
cervical cytological images. These data are used to construct screener
performance profiles, which have been compared to screener experience. The
experimental methodology is described and how the screener performance profile
is constructed. Results from a study of 10 screeners, checkers and pathologists
are presented showing predicted trends of human performance. Relations to
experience and strategy are also shown, though these relationships are not
statistically significant. A standardised quality assurance test is developed that
profiles screeners across many performance measures. Highly significant
correlations were found between fixation saliency and machine colour texture
(maxima density), though fixation saliency suffers from a lack of a significant
statistical basis. Further fixation data is needed, however if it conforms to the
existing trends then the results would support the new data validation method as a
framework from which image analysis techniques applied to cytology may be
objectively tested. Furthermore, this new approach to cervical cytology quality
assurance would have the potential to further reduce human errors in the cervical
smear inspection process by lowering levels of observer variation found in all
aspects of the cervical screening process
