Abstract:Deep learning is an important branch of a broader family of machine learning methods which attempt
to learn useful features from data by using a computational model with multilayer neural networks. A deep
learning network can form more abstract high-layer features through combination of the lower layer features to
find the complex intrinsic characteristics of the data. Convolutional neural network is one of most researched deep
networks because of its excellent performance in processing images. This paper firstly introduced the structural
characteristics and training methods of deep learning networks, followed by the convolutional neural network, and
finally discussed the application and development trend of deep learning network in the field of neuroimaging.
田苗,林岚,张柏雯,吴水才. 深度学习在神经影像中的应用研究[J]. 中国医疗设备, 2016, 31(12): 4-9.
TIAN Miao, LIN Lan,
ZHANG Bai-wen, WU Shui-cai. Study on the Application of Deep Learning in Neuroimaging. China Medical Devices, 2016, 31(12): 4-9.