Application of a pathomorphological image database in computer-aided cytological examinations

Authors:
B. D. Piętka;A. Dulewicz;P. Jaszczak;P. Kupis
Affiliations:
Laboratory of Computer-Aided Image Diagnostics Systems, Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland;Laboratory of Computer-Aided Image Diagnostics Systems, Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland;Laboratory of Computer-Aided Image Diagnostics Systems, Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland;Laboratory of Computer-Aided Image Diagnostics Systems, Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
Venue:
Machine Graphics & Vision International Journal - Special issue on Image Databases
Year:
2010

Citing 2
Cited 0

Selected algorithms for the computer analysis of microscope scans in the system for early detection of the urinary bladder cancer (poster session)

Technology and Health Care - Abstracts of ESEM 2001, The sixth biennial conference of the European Society for Engineering and Medicine, Belfast, Northern Ireland
Removing artefacts from microscopic images of cytological smears

Machine Graphics & Vision International Journal

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Abstract

The paper deals with the problem of early detection of bladder cancer based on non-invasive, voided urine cytological investigations. In spite of the diagnostic potential of the method for discovering malignancy associated changes in cells before they start to form a tumour, cytological tests seem to be underestimated by physicians, as there is a common view that their sensitivity, especially in early stages of the cancer, is relatively low. We depict here just one, but significant, direction of our work that aims to support the cytopathologist in making the diagnosis more accurate and reliable. The key idea relies on classification of adaptive smear objects by searching for similar patterns in a flexible pathomorphological image database using content-based image retrieval technology (CBIR).