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Multi-Channel brain atrophy pattern analysis in neuroimaging retrieval

机译:神经影像检索中的多通道脑萎缩图案分析

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The high throughput 3D neuroimaging datasets have posed great challenges for neuroimaging data retrieval. To achieve more accurate neuroimaging retrieval, various content-based retrieval approaches have been proposed. Recent studies showed a tendency of using the localized features extracted from a subset of the brain structures, instead of the global features extracted from whole brain. However, these studies relied heavily on specific pattern analysis techniques or clinical expertise. In this study we proposed a Multi-Channel pattern analysis approach to identify the most discriminative disease-sensitive brain structures for neurodegenerative disorders and thus to enhance neuroimaging retrieval. The preliminary results suggested that the proposed Multi-Channel pattern analysis approach could confidently identify the brain structures with atrophy and further improve the neuroimaging retrieval performance.
机译:高吞吐量3D神经影像数据集对神经影像数据检索构成了极大的挑战。为了实现更准确的神经影像测验检索,已经提出了各种基于内容的检索方法。最近的研究表明,使用从脑结构的子集中提取的局部特征的趋势,而不是从整个大脑中提取的全局特征。然而,这些研究严重依赖于具体的模式分析技术或临床专业知识。在这项研究中,我们提出了一种多通道模式分析方法来鉴定神经变性障碍最辨别的疾病敏感的脑结构,从而增强神经影像学检索。初步结果表明,所提出的多通道模式分析方法可以自信地识别萎缩的脑结构,进一步提高神经影像检索性能。

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