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http://dx.doi.org/10.7471/ikeee.2019.23.4.1408

Compressed-Sensing Cardiac CINE MRI using Neural Network with Transfer Learning  

Park, Seong-Jae (Dept. of Electrical Engineering, Kwangwoon University)
Yoon, Jong-Hyun (Neuroscience Research Institute Gachon University)
Ahn, Chang-Beom (Dept. of Electrical Engineering, Kwangwoon University)
Publication Information
Journal of IKEEE / v.23, no.4, 2019 , pp. 1408-1414 More about this Journal
Abstract
Deep artificial neural network with transfer learning is applied to compressed sensing cardiovascular MRI. Transfer learning is a method that utilizes structure, filter kernels, and weights of the network used in prior learning for current learning or application. The transfer learning is useful in accelerating learning speed, and in generalization of the neural network when learning data is limited. From a cardiac MRI experiment, with 8 healthy volunteers, the neural network with transfer learning was able to reduce learning time by a factor of more than five compared to that with standalone learning. Using test data set, reconstructed images with transfer learning showed lower normalized mean square error and better image quality compared to those without transfer learning.
Keywords
Compressed sensing; Deep learning; U-net; Transfer learning; Cardiovascular MRI;
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Times Cited By KSCI : 3  (Citation Analysis)
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