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论文:2015,Vol:33,Issue(3):516-523 |
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引用本文： |
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黄伟, 陈光. 一种改善动脉自旋标记磁共振图像中部分容积效应的新算法[J]. 西北工业大学学报 |
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Huang Wei, Chen Guang. A New Method to Correct Partial Volume Effect in ASL (Arterial Spin Labeling) Magnetic Resonance Images[J]. Northwestern polytechnical university |
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| 一种改善动脉自旋标记磁共振图像中部分容积效应的新算法 |
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| 黄伟1, 陈光2 |
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1. 南昌大学 信息工程学院, 浙江 南昌 330031;
2. 西安通信学院, 陕西 西安 710072 |
| 摘要: |
| 动脉自旋标记磁共振图像是一种新颖的无侵入式的功能性磁共振图像。这类图像可以直观测量患者大脑血流量,对揭示患者是否患有老年痴呆症及判断相应的病症程度十分有效。然而,动脉自旋标记图像本身的分辨率不高,再加上扫描过程中不可避免的信号相叉污染和像素异质性等问题,使得部分容积效应在该类图像中普遍存在。部分容积效应会造成动脉自旋标记图像中信号还原失真,进而影响患者大脑血流量测量,对其病症判断带来不利影响。在文章中,一种基于单像素点信息的新颖算法被提出,改善动脉自旋标记磁共振图像中的部分容积效应。大量的统计比较实验表明,该算法不仅能解决国际上现行的改善算法中不可避免的改善结果过度模糊、丢失大脑细节信息问题,还能对准确判断患者老年痴呆病症程度能起到积极作用。 |
| 关键词:
算法
有约束最优化
实验设计
诊断
拉格朗日乘数
线性回归
磁共振成像
最优化
信噪比
光谱分辨率
支持向量机
动脉自旋标记
大脑血流量
老年痴呆症
磁共振图像
部分容积效应
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| A New Method to Correct Partial Volume Effect in ASL (Arterial Spin Labeling) Magnetic Resonance Images |
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| Huang Wei1, Chen Guang2 |
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1. School of Information Engineering, Nanchang University, Nanchang, 330031, China;
2. Xi'an Communication Institute, Xi'an, 710072, China |
| Abstract: |
| ASL is a novel non-invasive modality in functional Magnetic Resonance Imaging (MRI). ASL is capable of directly reflecting the Cerebral Blood Flow (CBF) of scanned patients, and is helpful to doing two things: (1) determining whether the scanned patient suffers from the dementia disease or not; (2) if the patient does suffer from the disease, determining the severity of the disease. However, since the spectral resolution of ASL is not high and problems of signal cross-contamination as well as voxel heterogeneity exist in this modality, the problem of Partial Volume Effect (PVE) is commonly seen in ASL images. Moreover, PVE can easily deteriorate ASL signals, making the measured CBF of patients inaccurate and badly influencing their disease diagnosis thereafter. In this paper, a novel method solely based on single voxel information is introduced to correct PVE in ASL. Extensive experiments are conducted to suggest that this new method is not only capable of handling existing problems of blurring and brain detail loss which are commonly generated in conventional PVE correction methods but is also helpful to improving the precision of dementia disease diagnosis, from the statistical point of view. |
| Key words:
algorithms
constrained optimization
design of experiments
diagnosis
Lagrange multipliers
linear regression
magnetic resonance imaging
optimization
signal to noise ratio
spectral resolution
support vector machines
arterial spin labeling (ASL)
cerebral blood flow (CBF)
dementia
magnetic resonance image
partial volume effect (PVE)
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| 收稿日期: 2014-11-04
修回日期:
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| DOI: |
| 基金项目: 国家自然科学基金(61403182、61363046)、江西省(第九批)青年科学家(暨井冈之星)培养对象与教育部留学回国人员科研启动基金([2014]1685号)资助 |
| 通讯作者:
Email： |
| 作者简介: 黄伟(1983—),南昌大学副教授,主要从事医学图像处理研究。
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| 作者相关文章 |
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| 黄伟 在本刊中的所有文章 |
| 陈光 在本刊中的所有文章 |
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参考文献: |
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[1] Mahendra B. A Pathography of Dementia[J]. Dementia, 1987(1): 189-202
[2] Folstein M, Folstein S, McHung P. Mini-Mental State: A Practical Method for Grading the Cognitive State of Patients for the Clinician[J]. Journal of Psychiatric Research, 1975, 12(3): 189-198
[3] Cardenas V, Chao L, Studholme C, et al. Brain Atrophy Associated with Baseline and Longitudinal Measures of Cognition[J]. Neurobiology of Aging, 2011, 32(4): 572-580
[4] Wee C, Yap P, Denny K, et al. Resting-State Multi-Spectrum Functional Connectivity Networks for Identification of MCI Patients[J]. PLoS Computational Biology, 2012, 7(5): e37828
[5] Wee C, Yap P, Shen D. Prediction of Alzheimer's Disease and Mild Cognitive Impairment using Cortical Morphological Patterns[J]. Human Brain Mapping, 2013, 34(12): 3411-3425
[6] Liu M, Zhang D, Shen D. Ensemble Sparse Classification of Alzheimer's Disease[J]. Neuro Image, 2012, 60(2): 1106-1116
[7] Zhou L, Wang Y, Li Y, et al. Hierarchical Anatomical Brain Networks for MCI Prediction: Revisiting Volumetric Measures[J]. PLoS Computational Biology, 2011, 6(7): e21935
[8] Malpass K. Alzheimer Disease: Arterial Spin-Labeled MRI for Diagnosis and Monitoring of AD[J]. Nature Reviews Neurology, 2012, 8(1):3
[9] Chen Y, Wolk D, Reddin J, et al. Voxel-Level Comparison of Arterial Spin-Labeling Perfusion MRI and FDG-PET in Alzheimer Disease[J]. Neurology, 2011, 77(2): 1977-1985
[10] Asllani I, Borogovac A, Brown T. Regression Algorithm Correcting for Partial Volume Effects in Arterial Spin Labeling MRI[J]. Magnetic Resonance in Medicine, 2008, 60: 1362-1371
[11] Goldstein T, Osher S. The Split Bregman Method for L1 Regularized Problems[J]. UCLA CAM Report, 2008, 8(29): 1-21 |
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