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- W2479308053 abstract "This chapter presents novel approach fuzzy connectedness image segmentation with geometric moments (FCISGM) for digital imaging and communications in medicine (DICOM) image mining. As most of the medical imaging data is exchanged in DICOM format, this chapter focuses on the various methodologies available for DICOM image feature extraction and mining. The comparison of existing medical image mining approaches with the proposed FCISGM approach is provided in this chapter. After carrying out exhaustive results it has been found that proposed FCISGM method gives more precise results and requires minimum number of computations compare to other medical image mining approaches resulting in improved relevant outcomes." @default.
- W2479308053 created "2016-08-23" @default.
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- W2479308053 date "2017-01-01" @default.
- W2479308053 modified "2023-09-28" @default.
- W2479308053 title "Medical Image Mining Using Fuzzy Connectedness Image Segmentation" @default.
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- W2479308053 doi "https://doi.org/10.4018/978-1-5225-0983-7.ch011" @default.
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