Journal of Optoelectronics · Laser, Volume. 35, Issue 5, 490(2024)
Retinal vessel segmentation based on enhanced feature extraction
[1] [1] SHAH S,SHAHZAD A,KHAN A,et al.Unsupervised method for retinal vessel segmentation based on Gabor wavelet and multiscale line detector[J].IEEE Access,2019,(7):167221-167228.
[2] [2] CHAUDHURI S,CHATTERJEE S,KATZ N,et al.Detection of blood vessels in retinal images using two-dimensional matched filters[J].IEEE Transactions on Medical Imaging,1989,8(3):263-269.
[4] [4] FRAZ M M,REMAGNINO P,HOPPE A,et al.An ensemble classification-based approach applied to retinal blood vessel segmentation[J].IEEE Transactions on Biomedical Engineering,2012,59(9):2538-2548.
[5] [5] YAN Z,XIN Y,CHENG K T.Joint segment-level and pixel-wise losses for deep learning-based retinal vessel segmentation[J].IEEE Transactions on Biomedical Engineering,2018,65(9):1912-1923.
[7] [7] LI D,RAHARDJA S.BSEResU-Net:an attention-based before-activation residual U-Net for retinal vessel segmentation[J].Computer Methods and Programs in Biomedicine,2021,205:106070.
[9] [9] CHENG Y, MA M, ZHANG L, et al.Retinal blood vessel segmentation based on Densely Connected U-Net[J].Mathematical Biosciences and Engineering,2020,17(4):3088-3108.
[10] [10] RONNEBERGER O,FIsCHER P,BROX T.U-Net:convolutional networks for biomedical image segmentation[C]//Medical Image Computing and Computer-Assisted Intervention-MICCAI 2015,October 5-9,2015,Munich,Germany.Cham:Springer,2015,9351:234-241.
[11] [11] HE K M,ZHANG X Y,REN s Q,et al.Deep residual learning for image recognition[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR),June 27-30,2016, Las Vegas,NV,USA.New York:IEEE Press,2016:770778.
[12] [12] HE K M, ZHANG X Y, REN S Q, et al.Delving deep into rectifiers:surpassing human-level performance on imageNet classification[C]//2015 IEEE International Conference on Computer Vision (ICCV),December 7-13,2015,Santiago,Chile.New York: IEEE Press,2015:1026-1034.
[13] [13] CHEN L C,PAPANDREOU G,KOKKINOS I,et al.DeepLab:semantic image segmentation with deep convolutional nets,atrous convolution,and fully connected CRFs[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2018,40(4):834-848.
[14] [14] WOO S,PARK J,LEE J Y,et al.CBAM:convolutional block attention module[C]//2018 European Conference on Computer Vision (ECCV),September 10-13,2018,Munich,Germany.Heidelberg:Springer,2018:3-19.
[15] [15] OKTAY O,SCHLEMPER J,FOLGOC L L,et al.Attention U-Net:learning where to look for the pancreas[EB/OL].(2018-04-11)[2023-02-11].https://arxiv.org /abs/1804.03999.
[16] [16] MISRA D.Mish:A self regularized non-monotonic neural activation function[EB/OL].(2019-10-02)[2023-02-17].https://arxiv.org /abs/1908.08681.
[17] [17] SONALI,SIMA S,AMIT K S,et al.An approach for de-noising and contrast enhancement of retinal fundus image using CLAHE[J].Optics and Laser Technology,2018,110:87-98.
[19] [19] KHAN K B,KHALIQ A A,SHAHID M.A novel fast GLM approach for retinal vascular segmentation and denoising[J].Journal of Information Science and Engineering,2017,33(6):1611-1627.
[20] [20] YAN Z,XIN Y,CHENG K T.Joint segment-level and pixel-wise losses for deep learning-based retinal vessel segmentation[J].IEEE Transactions on Biomedical Engineering,2018,65(9):1912-1923.
[21] [21] ATLI I,GEDIK O S.Sine-Net:A fully convolutional deep learning architecture for retinal blood vessel segmentation[J].Engineering Science and Technology,an International Journal,2021,24(2):271-283.
[22] [22] TAMIM N,ELSHRKAWEY M,AZIM G A,et al.Retinal blood vessel segmentation using hybrid features and multi-layer perceptron neural networks[J].Symmetry,2020,12(6):894.
[23] [23] WU Y,XIA Y,SONG,Y,et al.NFN+:A novel network followed network for retinal vessel segmentation[J].Neural Networks,2020,126:153-162.
[24] [24] YUAN Y,ZHANG L,WANG L,et al.Multi-level attention network for retinal vessel segmentation[J].IEEE Journal of Biomedical and Health Informatics,2022,26(1):312-323.
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SUN Guodong, YAN Fengting, SHI Zhicai. Retinal vessel segmentation based on enhanced feature extraction[J]. Journal of Optoelectronics · Laser, 2024, 35(5): 490
Received: Feb. 17, 2023
Accepted: --
Published Online: Sep. 24, 2024
The Author Email: YAN Fengting (yanfengting2008@163.com)