Acta Optica Sinica, Volume. 38, Issue 4, 0410003(2018)
Low-Dose CT Image Denoising Method Based on Convolutional Neural Network
[7] Whiting B R. Signal statistics in X-ray computed tomography. [C]∥Medical Imaging 2002: Physics of Medical Imaging, International Society for Optics and Photonics, 4682, 53-61(2002).
[8] Xu Q. Statistical reconstruction methods for insufficient X-ray CT projection data Xi'an: Xi'an[D]. Jiaotong University(2012).
[10] Wu W W, Quan C, Liu F L. Filtered back-projection image reconstruction algorithm for opposite parallel linear CT scanning[J]. Acta Optica Sinica, 36, 0911009(2016).
[11] Li Z G, Li L, Han Y et al. A BPF-type reconstruction algorithm for circle-plus-line trajectory in cone beam CT[J]. Acta Optica Sinica, 36, 0911008(2016).
[12] Dong J W. The progress on research and principles of computed tomography iterative reconstruction[J]. China Medical Equipment, 13, 128-133(2016).
[13] Zhang T, Wang B, Yang L J et al. Low dose CT image enhancement based on second generation Curvelet transform[J]. Computer Engineering and Applications, 46, 191-193(2010).
[15] Kang D, Slomka P J, Nakazato R et al. Image denoising of low-radiation dose coronary CT angiography by an adaptive block-matching 3D algorithm. [C]∥ Proceedings of SPIE, 8669, 86692G(2013).
[17] Lecun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 521, 436-444(2015).
[18] Chen H, Zhang Y, Zhang W H et al. Low-dose CT denoising with convolutional neural network. [C]∥ Proceedings of IEEE 14th International Symposium on Biomedical Imaging, 143-146(2017).
[21] Ioffe S, Szegedy C. Batch normalization: accelerating deep network training by reducing internal covariate shift. [C]∥Proceedings of the 32nd International Conference on Machine Learning, 37, 448-456(2015).
[22] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition. [C]∥Processing of IEEE Conference on Computer Vision and Pattern Recognition, 770-778(2016).
[24] Huang G, Liu Z, Weinberger K Q et al. Densely connected convolutional networks. [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 4700-4708(2017).
[25] Kingma D P, Ba J. Adam: a method for stochastic optimization. [C]∥The 3rd International Conference on Learning Representations, 1-15(2015).
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Yungang Zhang, Benshun Yi, Chenyue Wu, Yu Feng. Low-Dose CT Image Denoising Method Based on Convolutional Neural Network[J]. Acta Optica Sinica, 2018, 38(4): 0410003
Category: Image Processing
Received: Sep. 15, 2017
Accepted: --
Published Online: Jul. 10, 2018
The Author Email: Zhang Yungang (zyg60714@126.com)