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Fusing Fuzzy and Probabilistic Memberships for White Matter Lesion Detection in MRI of the Brain

机译:对大脑MRI的白质病变检测融合模糊和概率隶属关系

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Computerized tools for automated detection of white matter lesions of the brain in magnetic resonance imaging are very useful for neuroscience researchers to enhance the study of brain-related diseases and their causal associations with other risk factors. We introduce in this paper a fusion approach for identifying white matter lesions in elderly subjects with structural brain tissue changes. The detection methodology is based on image segmentation methods and probabilistic models for membership assignments and fusion. Experimental results on image data of patients show the effectiveness of the proposed approach in comparisons with other detection models.
机译:用于自动检测磁共振成像的大脑的白质损伤的计算机化工具对于神经科学研究人员来说非常有用,以增强脑与脑相关疾病的研究及其与其他风险因素的因果关系。我们在本文中介绍了一种融合方法,用于鉴定具有结构脑组织变化的老年人受试者的白质病变。检测方法基于成员资格分配和融合的图像分段方法和概率模型。对患者图像数据的实验结果表明了拟议方法与其他检测模型的比较效果。

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