Medical Image Retrieval Using Vector Quantization and Fuzzy S-tree
作者： Jana Nowaková , Michal Prílepok , Václav Snášel
DOI: 10.1007/S10916-016-0659-2
关键词: Fuzzy logic 、 tf–idf 、 Image (mathematics) 、 Normalized compression distance 、 Data mining 、 Vector quantization 、 Image retrieval 、 Computer science 、 Contextual image classification 、 Tree (data structure) 、 Health informatics 、 Health Information Management 、 Medicine (miscellaneous) 、 Information Systems
摘要: The aim of the article is to present a novel method for fuzzy medical image retrieval (FMIR) using vector quantization (VQ) with signatures in conjunction S-trees. In past times, task similar pictures searching was not based on content (e.g. shapes, colour) but picture name. There exist some methods same purpose, there still space development more efficient methods. proposed system used finding images, our case area --- mammography, addition creation list images cases. created assessing nature whether malignant or benign. suggested compared Normalized Compression Distance (NCD) instead and S-tree. NCD useful cases malignancy assessment, it able capture interest image. going be added complex decision support help determine appropriate healthcare according experiences similar, previous
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