Dual-channel asymmetric convolutional neural network for an efficient retinal blood vessel segmentation in eye fundus images

Biocybernetics and Biomedical Engineering - Tập 42 - Trang 695-706 - 2022
Yanan Xu1, Yingle Fan1
1Laboratory of Pattern Recognition and Image Processing, Hangzhou Dianzi University, Hangzhou, China

Tài liệu tham khảo

Prasad Reddy, 2021, Blood vessel extraction in fundus images using hessian eigenvalues and adaptive thresholding, Evol Intel, 14, 577, 10.1007/s12065-019-00329-z Ramos-Soto, 2021, An efficient retinal blood vessel segmentation in eye fundus images by using optimized top-hat and homomorphic filtering, Comput Methods Prog Biomed, 201, 10.1016/j.cmpb.2021.105949 Tian, 2020, Multi-path convolutional neural network in fundus segmentation of blood vessels, Biocybern Biomed Eng, 40, 583, 10.1016/j.bbe.2020.01.011 Farokhian, 2017, Automatic parameters selection of Gabor filters with the imperialism competitive algorithm with application to retinal vessel segmentation, Biocybern Biomed Eng, 37, 246, 10.1016/j.bbe.2016.12.007 Tchinda, 2021, Retinal blood vessels segmentation using classical edge detection filters and the neural network, Inform Med Unlock, 23 Samuel, 2021, VSSC Net: Vessel Specific Skip chain Convolutional Network for blood vessel segmentation, Comput Methods Prog Biomed, 198, 10.1016/j.cmpb.2020.105769 Oliveira, 2018, Retinal vessel segmentation based on Fully Convolutional Neural Networks, Expert Syst Appl, 112, 229, 10.1016/j.eswa.2018.06.034 Li, 2021, Blood vessel segmentation of retinal image based on Dense-U-Net Network, Micromachines, 12, 1478, 10.3390/mi12121478 Liu, 2022, Multiscale U-Net with spatial positional attention for retinal vessel segmentation, J Healthc Eng, 2022, 1 Chaudhuri, 1989, Detection of blood vessels in retinal images using two-dimensional matched filters, IEEE Trans Med Imaging, 8, 263, 10.1109/42.34715 Hugo, 2018, Blood vessel segmentation in retinal fundus images using Gabor filters, fractional derivatives, and Expectation Maximization, Appl Math Comput, 339, 568 Luo, 2020, The comparison of retinal vessel segmentation methods in fundus images, J Phys Conf Ser, 1574, 10.1088/1742-6596/1574/1/012160 Delibasis, 2010, Automatic model-based tracing algorithm for vessel segmentation and diameter estimation, Comput Methods Prog Biomed, 99, 108, 10.1016/j.cmpb.2010.03.004 Zhao, 2018, Automatic retinal vessel segmentation using multi-scale superpixel chain tracking, Digit Signal Process, 81, 26, 10.1016/j.dsp.2018.06.006 Tian, 2021, Blood vessel segmentation of fundus retinal images based on improved frangi and mathematical morphology, Comput Math Methods Med, 2021, 1 Geetharamani, 2016, Retinal blood vessel segmentation employing image processing and data mining techniques for computerized retinal image analysis, Biocybern Biomed Eng, 36, 102, 10.1016/j.bbe.2015.06.004 Ding, 2021, A multichannel deep neural network for retina vessel segmentation via a fusion mechanism, Front Bioeng Biotech, 9, 10.3389/fbioe.2021.697915 Orlando, 2017, A discriminatively trained fully connected conditional random field model for blood vessel segmentation in fundus images, IEEE Trans Biomed Eng, 64, 16, 10.1109/TBME.2016.2535311 Fu, 2016, Retinal vessel segmentation via deep learning network and fully-connected conditional random fields, 698 Long, 2017, Fully convolutional networks for semantic segmentation, IEEE Trans Pattern Anal Mach Intell, 39, 640, 10.1109/TPAMI.2016.2572683 Ronneberger, 2015, U-net: Convolutional networks for biomedical image segmentation, Medical Image Comput Comput-Assisted Intervention, 9351, 234 Gu, 2019, CE-Net: Context encoder network for 2D medical image segmentation, IEEE Trans Med Imaging, 38, 2281, 10.1109/TMI.2019.2903562 Pan, 2019, A fundus retinal vessels segmentation scheme based on the improved deep learning U-Net model, IEEE Access, 7, 122634, 10.1109/ACCESS.2019.2935138 Cloutman, 2013, Interaction between dorsal and ventral processing streams: Where, when and how?, Brain Lang, 127, 251, 10.1016/j.bandl.2012.08.003 Pathan, 2019, Automated detection of optic disc contours in fundus images using decision tree classifier, Biocybern Biomed Eng, 40, 52, 10.1016/j.bbe.2019.11.003 Spratling, 2013, Image segmentation using a sparse coding model of cortical area V1, IEEE Trans Image Process, 22, 1631, 10.1109/TIP.2012.2235850 Fang, 2020, Cross-modal image fusion guided by subjective visual attention, Neurocomputing, 414, 333, 10.1016/j.neucom.2020.07.014 David, 2022, Retinal blood vessels and optic disc segmentation using U-Net, Math Probl Eng, 2022, 1, 10.1155/2022/8030954 Staal, 2004, Ridge-based vessel segmentation in color images of the retina, IEEE Trans Med Imaging, 23, 501, 10.1109/TMI.2004.825627 Fraz, 2012, An ensemble classification-based approach applied to retinal blood vessel segmentation, IEEE Trans Biomed Eng, 59, 2538, 10.1109/TBME.2012.2205687 Khan, 2022, Width-wise vessel bifurcation for improved retinal vessel segmentation, Biomed Signal Process Control, 71, 10.1016/j.bspc.2021.103169 Khawaja, 2019, A multi-scale directional line detector for retinal vessel segmentation, Sensors, 19, 4949, 10.3390/s19224949 Peng, 2018, Blood vessels segmentation by using CDNet, 305 Yan, 2018, Joint segment-level and pixel-wise losses for deep learning based retinal vessel segmentation, IEEE Trans Biomed Eng, 65, 1912, 10.1109/TBME.2018.2828137 Li, 2016, A Cross-modality Learning Approach for Vessel Segmentation in Retinal Images, IEEE Trans Med Imaging, 35, 109, 10.1109/TMI.2015.2457891