Human age estimation with surface-based features from MRI images

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 影像分析与机器视觉团队

	Human age estimation with surface-based features from MRI images
	Wang, Jieqiong; Dai, Dai; Li, Meng; Hua, Jing; *He, Huiguang
	2012
会议日期	2012/10/1
会议地点	美国
关键词	Age Estimation Age-based Brain Images Brain Networks Correlation Coefficient Cross Validation Data Sets Gaussian Curvatures Healthy Subjects Human Age Estimation Mean Absolute Error Mean Curvature Mri Image Regional Feature Regression Model Relevance Vector Machine Root Mean Squared Errors Surface Area Surface-based
英文摘要	Over the past years, many efforts have been made in the estimation of the physiological age based on the human MRI brain images. In this paper, we propose a novel regression model with surface-based features to estimate the human age automatically and accurately. First, individual regional surface-based features (thickness, mean curvature, Gaussian curvature and surface area) from the MRI image were extracted, which were subsequently used to construct combined regional features and the brain networks. Then, the individual regional surface-based features, brain network with surface-based features and combined regional surface-based features were used for age regression by relevance vector machine (RVM), respectively. In the experiment, a dataset of 360 healthy subjects aging from 20 to 82 years was used to evaluate the performance. Experimental results based on 10-fold cross validation show that, compared to the previous methods, age estimation model with combined surface-based features can yield a remarkably high accuracy (mean absolute error: 4.6 years and root mean squared error: 5.6 years) and a significantly high correlation coefficient (r = 0.94), which is the best age estimation result as far as we know and suggests that surface-based features are more powerful than other features used in previous methods for human age estimation.
会议录	3rd International Workshop on Machine Learning in Medical Imaging, MLMI 2012, Held in conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/20555]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_影像分析与机器视觉团队
推荐引用方式 GB/T 7714	Wang, Jieqiong,Dai, Dai,Li, Meng,et al. Human age estimation with surface-based features from MRI images[C]. 见:. 美国. 2012/10/1.