A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease

	A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease
	Peng, B.; S. H. Wang; Z. Y. Zhou; Y. Liu; B. T. Tong; T. Zhang and Y. K. Dai
	2017
发表期刊	Neuroscience Letters
卷号	651
摘要	Machine learning methods have been widely used in recent years for detection of neuroimaging biomarkers in regions of interest (ROIs) and assisting diagnosis of neurodegenerative diseases. The innovation of this study is to use multilevel-ROI-features-based machine learning method to detect sensitive morphometric biomarkers in Parkinson's disease (PD). Specifically, the low-level ROI features (gray matter volume, cortical thickness, etc.) and high-level correlative features (connectivity between ROIs) are integrated to construct the multilevel ROI features. Filter- and wrapper-based feature selection method and multi-kernel support vector machine (SVM) are used in the classification algorithm. Tl-weighted brain magnetic resonance (MR) images of 69 PD patients and 103 normal controls from the Parkinson's Progression Markers Initiative (PPMI) dataset are included in the study. The machine learning method performs well in classification between PD patients and normal controls with an accuracy of 85.78%, a specificity of 87.79%, and a sensitivity of 87.64%. The most sensitive biomarkers between PD patients and normal controls are mainly distributed in frontal lobe, parental lobe, limbic lobe, temporal lobe, and central region. The classification performance of our method with multilevel ROI features is significantly improved comparing with other classification methods using single-level features. The proposed method shows promising identification ability for detecting morphometric biomarkers in PD, thus confirming the potentiality of our method in assisting diagnosis of the disease. (C) 2017 Elsevier B.V. All rights reserved.
收录类别	sci ; ei
语种	英语
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/59151
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Peng, B.,S. H. Wang,Z. Y. Zhou,et al. A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease[J]. Neuroscience Letters,2017,651.
APA	Peng, B.,S. H. Wang,Z. Y. Zhou,Y. Liu,B. T. Tong,&T. Zhang and Y. K. Dai.(2017).A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease.Neuroscience Letters,651.
MLA	Peng, B.,et al."A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease".Neuroscience Letters 651(2017).

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