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EN
The paper deals with an image database organization and utilization in computer-aided cytology. To illustrate the idea we take as an example the problem of bladder cancer early detection based on urine cytology. In spite of its diagnostic potential for discovering malignancy associated changes (MAC) at the cell level it seems to be underestimated. There is common view that sensitivity of the method, especially for early cancer stages, is relatively low. We depict here just one but significant direction of our works that aims to support pathologists making the diagnosis more accurate and reliable. The key idea relies on automatic searching for MAC by comparing nuclear chromatin structure of objects in a smear with a collection of sample patterns contained in a pathomorphological image database.
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Content available remote Computer-aided analysis of serial images
EN
There is described a concept and basic procedures of computer analysis of serial images (ASI) stored in image databases (IDB). ASI is considered as a series of computer procedures recognising some relations amonge image-records stored in IDB. The relations can be described both on same vectors of parameters assigned to the records and on the images themselves. Three basic groups of relations are considered: similarity, ordering and some higher-order relations described as hyperrelations of the MATCH - and SPREAD - type. Special attetion also has been paid to the semiordering of image- records based on the concept of semiordered linear vector spaces (Kantorovitsh spaces); this is considered as a general method of multi-aspect evaluation of image-records. Some concepts of ASI described in the paper have been realsed in e system APOS, compatible whit a standard library of image processing procedures and an IDB management system. APOS has been designed mainly for biomedical applications.
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