A Bayesian Neo-Normal Mixture Model (Nenomimo) for MRI-Based Brain Tumor Segmentation

A Bayesian Neo-Normal Mixture Model (Nenomimo) for MRI-Based Brain Tumor Segmentation

The detection of a brain tumor through magnetic resonance imaging (MRI) is still challenging when the image is in low quality. Image segmentation could be done to provide a clear brain tumor area as the region of interest. In this study, we propose an improved model-based clustering approach for MRI...

書誌詳細
主要な著者:	Anindya Apriliyanti Pravitasari, Nur Iriawan, Kartika Fithriasari, Santi Wulan Purnami, Irhamah, Widiana Ferriastuti
フォーマット:	論文
言語:	English
出版事項:	MDPI AG 2020-07-01
シリーズ:	Applied Sciences
主題:	MRI image segmentation neo-normal mixture model Bayesian MCMC
オンライン･アクセス:	https://www.mdpi.com/2076-3417/10/14/4892

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