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1 2008

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Removing artefacts from microscopic images of cytological smears

Piętka B. D., Dulewicz A., Jaszczak P.

Machine Graphics and Vision

2008

Vol. 17, No. 1/2

131-152

This paper gives an overview of authors' attempts to design a computer-assisted urine smear screening system, focusing on the nastiest issues hampering its successful practical implementation. There are many valuable works concerning more or less sophisticated image processing and data mining algorithms which are capable of automatically detecting pathological morphology of cytological objects and distinguishing them from normal ones. Unfortunately, most of the attempts to implement those smart ideas in real world are likely to fail because of one but fundamental obstacle - artefacts. If not properly identified and removed from the analysis, they tend to generate so many false-positive warnings that the automated support is going to be useless because of its dramatically low specificity. Our paper addresses this neglected problem, trying to point out some general rules and implementation details that should be followed to reduce the influence of artefacts on overall system performance.