Computed Tomography (CT) Image Quality Enhancement via a Uniform Framework Integrating Noise Estimation and Super-Resolution Networks
暂无分享,去创建一个
Yifei Zhang | Ying Wang | Chengdong Wu | Xiaosheng Yu | Jianning Chi | Chengdong Wu | Xiaosheng Yu | Jianning Chi | Ying Wang | Yifei Zhang
[1] Christian Ledig,et al. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Kyoung Mu Lee,et al. Enhanced Deep Residual Networks for Single Image Super-Resolution , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[3] Eric Dubois,et al. Fast and reliable structure-oriented video noise estimation , 2005, IEEE Transactions on Circuits and Systems for Video Technology.
[4] J. R. Palta,et al. SU‐GG‐T‐124: Probability Density Distribution of Proton Range as a Function of Noise in CT Images , 2008 .
[5] Yu Zhang,et al. Very deep convolutional networks for end-to-end speech recognition , 2016, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[6] Foroohar Foroozan,et al. Microbubble Localization for Three-Dimensional Superresolution Ultrasound Imaging Using Curve Fitting and Deconvolution Methods , 2018, IEEE Transactions on Biomedical Engineering.
[7] Jing Tian,et al. Image Noise Estimation Using A Variation-Adaptive Evolutionary Approach , 2012, IEEE Signal Processing Letters.
[8] Abdul Rahman Ramli,et al. Computer-Assisted Diagnosis System for Breast Cancer in Computed Tomography Laser Mammography (CTLM) , 2017, Journal of Digital Imaging.
[9] Soosan Beheshti,et al. Adaptive Noise Variance Estimation in BayesShrink , 2010, IEEE Signal Processing Letters.
[10] David Zhang,et al. A comprehensive evaluation of full reference image quality assessment algorithms , 2012, 2012 19th IEEE International Conference on Image Processing.
[11] Yao Zhao,et al. Simultaneous color-depth super-resolution with conditional generative adversarial networks , 2019, Pattern Recognit..
[12] Daniel Rueckert,et al. Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Chengdong Wu,et al. Recombined Convolutional Neural Network for Recognition of Macular Disorders in SD-OCT Images , 2018, 2018 37th Chinese Control Conference (CCC).
[14] Yunjin Chen,et al. Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[15] Lei Zheng,et al. Image Noise Level Estimation by Principal Component Analysis , 2013, IEEE Transactions on Image Processing.
[16] Alessandro Foi,et al. Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering , 2007, IEEE Transactions on Image Processing.
[17] Shutao Li,et al. Hyperspectral Image Super-Resolution via Non-local Sparse Tensor Factorization , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Jie Wu,et al. Multiple-image super resolution using both reconstruction optimization and deep neural network , 2017, 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP).
[19] Xiaoou Tang,et al. Accelerating the Super-Resolution Convolutional Neural Network , 2016, ECCV.
[20] Muyinatu A. Lediju Bell,et al. Photoacoustic Source Detection and Reflection Artifact Removal Enabled by Deep Learning , 2018, IEEE Transactions on Medical Imaging.
[21] Yu-Bin Yang,et al. Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections , 2016, ArXiv.
[22] Meisam Rakhshanfar,et al. Estimation of Gaussian, Poissonian–Gaussian, and Processed Visual Noise and Its Level Function , 2016, IEEE Transactions on Image Processing.
[23] Farzad Zargari,et al. Explicit Ringing Removal in Image Deblurring , 2018, IEEE Transactions on Image Processing.
[24] Jean-Michel Morel,et al. A non-local algorithm for image denoising , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[25] David C. Alsop,et al. Using Anatomic Magnetic Resonance Image Information to Enhance Visualization and Interpretation of Functional Images: A Comparison of Methods Applied to Clinical Arterial Spin Labeling Images , 2017, IEEE Transactions on Medical Imaging.
[26] Wangmeng Zuo,et al. Learning a Single Convolutional Super-Resolution Network for Multiple Degradations , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[27] Robert L. Stevenson,et al. Extraction of high-resolution frames from video sequences , 1996, IEEE Trans. Image Process..
[28] Sergey Ioffe,et al. Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning , 2016, AAAI.
[29] H. Sebastian Seung,et al. Natural Image Denoising with Convolutional Networks , 2008, NIPS.
[30] Yun Fu,et al. Residual Dense Network for Image Super-Resolution , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[31] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[32] Haidawati Nasir,et al. Singular value decomposition based fusion for super-resolution image reconstruction , 2011, 2011 IEEE International Conference on Signal and Image Processing Applications (ICSIPA).
[33] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[34] Lin Wang,et al. An Improved Approach to the Cubic-Spline Interpolation , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).
[35] Marcos Martín-Fernández,et al. Automatic noise estimation in images using local statistics. Additive and multiplicative cases , 2009, Image Vis. Comput..
[36] Ping Jiang,et al. Fast and reliable noise level estimation based on local statistic , 2016, Pattern Recognit. Lett..
[37] R. Keys. Cubic convolution interpolation for digital image processing , 1981 .
[38] Stephen M. Moore,et al. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository , 2013, Journal of Digital Imaging.
[39] Jing-Yu Yang,et al. Image noise estimation and removal considering the bayer pattern of noise variance , 2017, 2017 IEEE International Conference on Image Processing (ICIP).
[40] Michael Elad,et al. Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries , 2006, IEEE Transactions on Image Processing.
[41] Xuanqin Mou,et al. Low-Dose CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss , 2017, IEEE Transactions on Medical Imaging.
[42] Li Fei-Fei,et al. Perceptual Losses for Real-Time Style Transfer and Super-Resolution , 2016, ECCV.