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	Automatic Recognition of Mild Cognitive Impairment from MRI Images Using Expedited Convolutional Neural Networks
	Wang shuqiang; Shen yanyan; Chen wei; Xiao tengfei; Hu jinxing
	2017
会议日期	2017
英文摘要	Few studies have focused on the potential of applying deep learning algorithms into magnetic resonance imaging (MRI) for automatic recognition of subjects with mild cognitive impairment (MCI). In this work, we propose the expedited convolutional neural networks involving Tucker decomposition to recognize MCI using MRI images. We employ transfer learning and data augmentation to deal with limited training data. The effect of Tucker decomposition on saving computational time is discussed. The experimental results show that the proposed model outperforms the previous methods. The expedited convolutional neural networks can provide a good guidance for the applications of deep learning in real-world classification with large training dataset.
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12639]
专题	深圳先进技术研究院_数字所
作者单位	2017
推荐引用方式 GB/T 7714	Wang shuqiang,Shen yanyan,Chen wei,et al. Automatic Recognition of Mild Cognitive Impairment from MRI Images Using Expedited Convolutional Neural Networks[C]. 见:. 2017.

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