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- W2327778540 abstract "In this article, we have studied the brain tumor’s features and those possible measuring features. For this, we focus on the analysis on GMM features obtained from weighted T1, T2 and the FLAIR MR images. The GMM method based methods have been mentioned in the literatures related to face identification, the literatures have a method that can provide the best compromise among complication, robustness and distinguishing degree, in addition, the literature conducts identification of speakers through feature and score normalization technology. Different from others, this article uses GMM in order to extract the sub-feature of each GMM. The decision tree is used for the appraisal of the classifying technology of GMM feature’s function, during our study, it is reflected on the brain tumor and the normal brain MR image’s identifying ability. This article conducts appraisal on the algorithm’s function by distinguishing the tumor images from non-tumor MR images." @default.
- W2327778540 created "2016-06-24" @default.
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- W2327778540 date "2016-01-16" @default.
- W2327778540 modified "2023-09-27" @default.
- W2327778540 title "Tumor Diagnosis Based on the GMM Feature Decision Classification" @default.
- W2327778540 cites W1972928435 @default.
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- W2327778540 doi "https://doi.org/10.14257/astl.2016.121.53" @default.
- W2327778540 hasPublicationYear "2016" @default.
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