|
|
Prostate Cancer Recognition Algorithm Based on Deep Learning |
Zhang Haowei*, Ren Xiaoqian, Liu Ying, Lou Yunzhong |
(School of Medical Instrument and Food Engineering,University of Shanghai for Science and Technology, Shanghai 200093, China) |
|
[1] Chen Wanqing, Sun Kexin, Zheng Rongshou,et al. Cancer incidence and mortality in China 2014[J]. Chinese Journal of Cancer Research, 2018,30(1):1-12. [2] Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018[J].A Cancer Journal for Clinicians,2018(68),7-30. [3] Aytekin O. Prostate MR imaging[J]. Radiologic Clinics of North America, 2018,56(2):13-13. [4] Esteva A,Kuprel B,Novoa RA,et al. Dermatologist-level classification of skin cancer with deep neural networks[J]. Nature,2017, 542: 115-118. [5] Liu Y, Gadepalli K, Norouzi M, et al. Detecting cancer metastases on gigapixel pathology images[J]. arXiv 2017,1703.02442. [6] Hinton GE, Salakhutdinov RR. Reducing the dimensionality of data with neural network[J]. Science,2006,313 (5786):504-507. [7] Wang Xiaogang. Deep learning in imagination[J].Communications of the CCE,2015,11(8):15-23. [8] Krizhevsky A, Sutskever I, Hinton GE. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 2017,60(6):84-90. [9] Jarrett K, Kavukcuoglu K, Ranzato M, et al. What is the best multi-stage architecture for object recognition?[C]//IEEE International Conference on Computer Vision. Kyota: IEEE, 2009:2146-2153. [10] 孙冬梅,陆剑锋,张善卿. 一种改进CLAHE算法在医学试纸条图像增强中的应用[J]. 中国生物医学工程学报,2016,35(4):502-506. |
|
|
|