Brain Tumour Segmentation from Multispectral MR Image Data Using Ensemble Learning Methods
作者： Ágnes Győrfi , Levente Kovács , László Szilágyi
DOI: 10.1007/978-3-030-33904-3_30
关键词:
摘要: The number of medical imaging devices is quickly and steadily rising, generating an increasing amount image records day by day. qualified human experts able to handle this data cannot follow trend, so there a strong need develop reliable automatic segmentation decision support algorithms. Brain Tumor Segmentation Challenge (BraTS), first organized seven years ago, provoked intensification the development brain tumor detection Beside many others, several ensemble learning solutions have been proposed lately above mentioned problem. This study presents evaluation framework developed evaluate accuracy efficiency these algorithms deployed in segmentation, based on BraTS 2016 train set. All evaluated proved suitable provide acceptable but random forest was found best, both terms precision efficiency.
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