Acta Optica Sinica, Volume. 43, Issue 20, 2010002(2023)
Unsupervised Denoising of Retinal OCT Images Based on Deep Learning
[1] Huang D, Swanson E A, Lin C P et al. Optical coherence tomography[J]. Science, 254, 1178-1181(1991).
[2] Drexler W, Morgner U, Ghanta R K et al. Ultrahigh-resolution ophthalmic optical coherence tomography[J]. Nature Medicine, 7, 502-507(2001).
[3] Cukras C, Wang Y D, Meyerle C B et al. Optical coherence tomography-based decision making in exudative age-related macular degeneration: comparison of time- vs spectral-domain devices[J]. Eye, 24, 775-783(2010).
[4] Virgili G, Menchini F, Casazza G et al. Optical coherence tomography (OCT) for detection of macular oedema in patients with diabetic retinopathy[J]. The Cochrane Database of Systematic Reviews, 1, CD008081(2015).
[5] Zhu X N, Mao Y X, Liang Y M et al. Noise analyses of optical coherence tomography systems (Ⅱ): Fourier domain and time domain OCT systems[J]. Acta Photonica Sinica, 36, 457-461(2007).
[6] He Q Y, Li Z L, Wang X Z et al. Automated retinal layer segmentation based on optical coherence tomographic images[J]. Acta Optica Sinica, 36, 1011003(2016).
[7] Balasubramanian M, Bowd C, Vizzeri G et al. Effect of image quality on tissue thickness measurements obtained with spectral domain-optical coherence tomography[J]. Optics Express, 17, 4019-4036(2009).
[8] Yuan Z L, Chen J B, Huang W Y et al. Speckle noise reduction of optical coherence tomography based on robust principle component analysis algorithm[J]. Acta Optica Sinica, 38, 0511002(2018).
[9] Deshpande S D, Er M H, Venkateswarlu R et al. Max-mean and max-median filters for detection of small targets[J]. Proceedings of SPIE, 3809, 74-83(1999).
[10] Deng G, Cahill L W. An adaptive Gaussian filter for noise reduction and edge detection[C], 1615-1619(2002).
[11] Aum J, Kim J H, Jeong J. Effective speckle noise suppression in optical coherence tomography images using nonlocal means denoising filter with double Gaussian anisotropic kernels[J]. Applied Optics, 54, D43-D50(2015).
[12] Chong B, Zhu Y K. Speckle reduction in optical coherence tomography images of human finger skin by wavelet modified BM3D filter[J]. Optics Communications, 291, 461-469(2013).
[13] Mayer M A, Borsdorf A, Wagner M et al. Wavelet denoising of multiframe optical coherence tomography data[J]. Biomedical Optics Express, 3, 572-589(2012).
[14] Zhang A Q, Xi J F, Sun J T et al. Pixel-based speckle adjustment for noise reduction in Fourier-domain OCT images[J]. Biomedical Optics Express, 8, 1721-1730(2017).
[15] Fang L Y, Li S T, Nie Q et al. Sparsity based denoising of spectral domain optical coherence tomography images[J]. Biomedical Optics Express, 3, 927-942(2012).
[16] Baghaie A, Yu Z Y, D’Souza R M. Involuntary eye motion correction in retinal optical coherence tomography: hardware or software solution?[J]. Medical Image Analysis, 37, 129-145(2017).
[17] Qu H, Wang Y, Lou S L et al. Speckle decorrelation optical coherence tomography with pure random phase plate[J]. Acta Optica Sinica, 43, 0111002(2023).
[18] Gulshan V, Peng L, Coram M et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs[J]. JAMA, 316, 2402-2410(2016).
[19] Sun Z, Wang S Y. Application of deep learning in intravascular optical coherence tomography[J]. Laser & Optoelectronics Progress, 59, 2200002(2022).
[20] Ma Y H, Chen X J, Zhu W F et al. Speckle noise reduction in optical coherence tomography images based on edge-sensitive cGAN[J]. Biomedical Optics Express, 9, 5129-5146(2018).
[21] Ronneberger O, Fischer P, Brox T. U-net: convolutional networks for biomedical image segmentation[M]. Navab N, Hornegger J, Wells W M, et al. Medical image computing and computer-assisted intervention–MICCAI 2015, 9351, 234-241(2015).
[23] Qiu B, Huang Z Y, Liu X et al. Noise reduction in optical coherence tomography images using a deep neural network with perceptually-sensitive loss function[J]. Biomedical Optics Express, 11, 817-830(2020).
[24] Zhang K, Zuo W M, Chen Y J et al. Beyond a Gaussian denoiser: residual learning of deep CNN for image denoising[J]. IEEE Transactions on Image Processing, 26, 3142-3155(2017).
[25] Dai H, Yang Y L, Yue X et al. Denoising method of retinal OCT images based on modularized denoising autoencoder[J]. Acta Optica Sinica, 43, 0110001(2023).
[27] Gisbert G, Dey N, Ishikawa H et al. Improved denoising of optical coherence tomography via repeated acquisitions and unsupervised deep learning[J]. Investigative Ophthalmology & Visual Science, 61, PB0035(2020).
[28] Huang Y, Zhang N, Hao Q. Real-time noise reduction based on ground truth free deep learning for optical coherence tomography[J]. Biomedical Optics Express, 12, 2027-2040(2021).
[30] Guo M H, Xu T X, Liu J J et al. Attention mechanisms in computer vision: a survey[J]. Computational Visual Media, 8, 331-368(2022).
[31] Wang P Q, Chen P F, Yuan Y et al. Understanding convolution for semantic segmentation[C], 1451-1460(2018).
[32] Tai Y, Yang J, Liu X M et al. MemNet: a persistent memory network for image restoration[C], 4549-4557(2017).
[34] Fang L Y, Li S T, McNabb R P et al. Fast acquisition and reconstruction of optical coherence tomography images via sparse representation[J]. IEEE Transactions on Medical Imaging, 32, 2034-2049(2013).
[35] Wu D F, Kim K, Li Q Z. Low-dose CT reconstruction with Noise2Noise network and testing-time fine-tuning[J]. Medical Physics, 48, 7657-7672(2021).
[36] Qiu B, You Y F, Huang Z Y et al. N2NSR-OCT: simultaneous denoising and super-resolution in optical coherence tomography images using semisupervised deep learning[J]. Journal of Biophotonics, 14, e202000282(2021).
Get Citation
Copy Citation Text
Guangyi Wu, Zhuoqun Yuan, Yanmei Liang. Unsupervised Denoising of Retinal OCT Images Based on Deep Learning[J]. Acta Optica Sinica, 2023, 43(20): 2010002
Category: Image Processing
Received: Mar. 27, 2023
Accepted: May. 6, 2023
Published Online: Oct. 23, 2023
The Author Email: Yanmei Liang (ymliang@nankai.edu.cn)