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In this paper, we present a novel neural network architecture for retinal vessel segmentation that improves over the state of the art on two benchmark datasets, is the first to run in real time on high resolution images, and its small memory and processing requirements make it deployable in mobile and embedded systems.
A new scientific method of identification
C. Simon and I. Goldstein · 1935
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Methods for evaluation of retinal microvascular abnormalities associated with hypertension/sclerosis in the atherosclerosis risk in communities study11the authors have no proprietary interest in the equipment and techniques described in this article
L. D. Hubbard, R. J. Brothers, W. N. King, L. X. Clegg, R. Klein, L. S. Cooper, A. R. Sharrett, M. D. Davis, and J. Cai · 1999
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Ridge-based vessel segmentation in color images of the retina
J. Staal, M. D. Abramoff, M. Niemeijer, M. A. Viergever, and B. v. Ginneken · 2004
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Personal authentication using digital retinal images
C. Mariño, M. G. Penedo, M. Penas, M. J. Carreira, and F. Gonzalez · 2006
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Personal verification based on extraction and characterisation of retinal feature points
M. Ortega, M. G. Penedo, J. Rouco, N. Barreira, and M. J. Carreira · 2009
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Retinal Imaging and Image Analysis
M. D. Abramoff, M. K. Garvin, and M. Sonka · 2010
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Retinal recognition: Personal identification using blood vessels
M. U. Akram, A. Tariq, and S. A. Khan · 2011
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A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features
D. Marin, A. Aquino, M. E. Gegundez-Arias, and J. M. Bravo · 2011
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An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation
M. M. Fraz, P. Remagnino, A. Hoppe, B. Uyyanonvara, A. R. Rudnicka, C. G. Owen, and S. A. Barman · 2012
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Robust Vessel Segmentation in Fundus Images, 2013
A. Budai, R. Bock, A. Maier, J. Hornegger, and G. Michelson · 2013
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Automatic no-reference quality assessment for retinal fundus images using vessel segmentation
T. Kohler, A. Budai, M. F. Kraus, J. Odstrcilik, G. Michelson, and J. Hornegger · 2013
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Retinal vessel segmentation by improved matched filtering: evaluation on a new high-resolution fundus image database
J. Odstrcilik, R. Kolar, A. Budai, J. Hornegger, J. Jan, J. Gazarek, T. Kubena, P. Cernosek, O. Svoboda, and E. Angelopoulou · 2013
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Retina based biometric authentication using phase congruency
M. I. Ahmed, M. A. Amin, B. Poon, and H. Yan · 2014
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GPU-based segmentation of retinal blood vessels
F. Argüello, D. L. Vilariño, D. B. Heras, and A. Nieto · 2014
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A high performance hardware architecture for portable, low-power retinal vessel segmentation
D. Koukounis, C. Ttofis, A. Papadopoulos, and T. Theocharides · 2014
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Rigid-motion scattering for image classification
L. Sifre · 2014
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Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan and A. Zisserman · 2014
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Trainable COSFIRE filters for vessel delineation with application to retinal images
G. Azzopardi, N. Strisciuglio, M. Vento, and N. Petkov · 2015
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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U-Net: Convolutional Networks for Biomedical Image Segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
Cited alongside, same era.
Blood Vessel Segmentation of Fundus Images by Major Vessel Extraction and Subimage Classification
S. Roychowdhury, D. D. Koozekanani, and K. K. Parhi · 2015
Cited alongside, same era.
original-date: 2016-08-13T05:26:41Z
Smartphone-Based Accurate Analysis of Retinal Vasculature towards Point-of-Care Diagnostics
X. Xu, W. Ding, X. Wang, R. Cao, M. Zhang, P. Lv, and F. Xu · 2016
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Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores
J. Zhang, B. Dashtbozorg, E. Bekkers, J. P. W. Pluim, R. Duits, and B. M. t. H. Romeny · 2016
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Augmentor: An Image Augmentation Library for Machine Learning
M. D. Bloice, C. Stocker, and A. Holzinger · 2017
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Fast accurate and robust retinal vessel segmentation system
Z. Jiang, J. Yepez, S. An, and S. Ko · 2017
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A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images
J. I. Orlando, E. Prokofyeva, and M. B. Blaschko · 2017
Later among the works it cites.
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pytorch: Tensors and Dynamic neural networks in Python with strong GPU acceleration, Aug. 2018 · 2016
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Leveraging Multiscale Hessian-Based Enhancement With a Novel Exudate Inpainting Technique for Retinal Vessel Segmentation
R. Annunziata, A. Garzelli, L. Ballerini, A. Mecocci, and E. Trucco · 2016
Cited alongside, same era.
Flexible architectures for retinal blood vessel segmentation in high-resolution fundus images
H. Bendaoudi, F. Cheriet, A. Manraj, H. Ben Tahar, and J. M. P. Langlois · 2016
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Acceleration package for neural networks on multi-core CPUs: Maratyszcza/NNPACK, Oct. 2018
M. Dukhan · 2016
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Automated retina identification based on multiscale elastic registration
I. N. Figueiredo, S. Moura, J. S. Neves, L. Pinto, S. Kumar, C. M. Oliveira, and J. D. Ramos · 2016
Cited alongside, same era.
DeepVessel: Retinal Vessel Segmentation via Deep Learning and Conditional Random Field
H. Fu, Y. Xu, S. Lin, D. W. Kee Wong, and J. Liu · 2016
Cited alongside, same era.
A Cross-Modality Learning Approach for Vessel Segmentation in Retinal Images
Q. Li, B. Feng, L. Xie, P. Liang, H. Zhang, and T. Wang · 2016
Cited alongside, same era.
A real-time fuzzy morphological algorithm for retinal vessel segmentation
P. Bibiloni, M. González-Hidalgo, and S. Massanet · 2018
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EyeSLAM: Real-time simultaneous localization and mapping of retinal vessels during intraocular microsurgery
D. Braun, S. Yang, J. N. Martel, C. N. Riviere, and B. C. Becker · 2018
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TVM: An Automated End-to-End Optimizing Compiler for Deep Learning
T. Chen, T. Moreau, Z. Jiang, L. Zheng, E. Yan, M. Cowan, H. Shen, L. Wang, Y. Hu, L. Ceze, C. Guestrin, and A. Krishnamurthy · 2018
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Clinically applicable deep learning for diagnosis and referral in retinal disease
J. D. Fauw, J. R. Ledsam, B. Romera-Paredes, S. Nikolov, N. Tomasev, S. Blackwell, H. Askham, X. Glorot, B. O’Donoghue, D. Visentin, G. v. d. Driessche, B. Lakshminarayanan, C. Meyer, F. Mackinder, S. Bouton, K. Ayoub, R. Chopra, D. King, A. Karthikesalingam, C. O. Hughes, R. Raine, J. Hughes, D. A. Sim, C. Egan, A. Tufail, H. Montgomery, D. Hassabis, G. Rees, T. Back, P. T. Khaw, M. Suleyman, J. Cornebise, P. A. Keane, and O. Ronneberger · 2018
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TernausNetV2: Fully Convolutional Network for Instance Segmentation
V. Iglovikov, S. Seferbekov, A. Buslaev, and A. Shvets · 2018
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Fixing Weight Decay Regularization in Adam
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ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentation
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M. Sandler, A. G. Howard, M. Zhu, A. Zhmoginov, and L.-C. Chen · 2018
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Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation
Z. Yan, X. Yang, and K. Cheng · 2018
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