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With the advent and great advances of methods based on deep learning in image analysis, it appears that they can be effective in digital pathology to support the work of pathologists. However, a major limitation in the development of computer-aided diagnostic systems for pathology is the cost of data annotation. Evaluation of tissue (histopathological) and cellular (cytological) specimens seems to be a complex challenge. To simplify the laborious process of obtaining a sufficiently large set of data, a number of different systems could be used for image annotation. Some of these systems are reviewed in this paper with a comparison of their capabilities.
Wydawca
Czasopismo
Rocznik
Tom
Strony
1436--1453
Opis fizyczny
Bibliogr. 97 poz., rys., tab.
Twórcy
autor
- Laboratory of Processing and Analysis of Microscopic Images, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland
autor
- Laboratory of Processing and Analysis of Microscopic Images, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland
autor
- Laboratory of Processing and Analysis of Microscopic Images, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland
autor
- Laboratory of Processing and Analysis of Microscopic Images, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland; Medical Pathomorphology Department, Medical University of Bialystok, Bialystok, Poland
Bibliografia
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Bibliografia
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