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dc.contributor.authorNowaková, Jana
dc.contributor.authorPrílepok, Michal
dc.contributor.authorSnášel, Václav
dc.identifier.citationJournal of Medical Systems. 2017, vol. 41, issue 2, art. no. 18.cs
dc.description.abstractThe aim of the article is to present a novel method for fuzzy medical image retrieval (FMIR) using vector quantization (VQ) with fuzzy signatures in conjunction with fuzzy S-trees. In past times, a task of similar pictures searching was not based on searching for similar content (e.g. shapes, colour) of the pictures but on the picture name. There exist some methods for the same purpose, but there is still some space for development of more efficient methods. The proposed image retrieval system is used for finding similar images, in our case in the medical area - in mammography, in addition to the creation of the list of similar images - cases. The created list is used for assessing the nature of the finding - whether the medical finding is malignant or benign. The suggested method is compared to the method using Normalized Compression Distance (NCD) instead of fuzzy signatures and fuzzy S-tree. The method with NCD is useful for the creation of the list of similar cases for malignancy assessment, but it is not able to capture the area of interest in the image. The proposed method is going to be added to the complex decision support system to help to determine appropriate healthcare according to the experiences of similar, previous cases.cs
dc.relation.ispartofseriesJournal of Medical Systemscs
dc.rights© Springer Science+Business Media New York 2016cs
dc.subjectvector quantizationcs
dc.subjectimage comparisoncs
dc.subjectimage classificationcs
dc.subjectfuzzy S-treecs
dc.titleMedical image retrieval using vector quantization and fuzzy S-treecs
dc.description.sourceWeb of Sciencecs
dc.description.firstpageart. no. 18cs

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