Page 125 - Computational Retinal Image Analysis

118 CHAPTER 6 Retinal vascular analysis: Segmentation, tracing, and beyond

[109] S. Tamura, Y. Okamoto, K. Yanashima, Zero-crossing interval correction in tracing eye-
fundus blood vessels, Pattern Recogn. 21 (3) (1988) 227–233.
[110] A. Can, H. Shen, J. Taylor, H. Tanenbaum, B. Roysam, Rapid automated tracing and
feature extraction from retinal fundus images using direct exploratory algorithm, IEEE
Trans. Inf. Tech. Biomed. 3 (2) (1999) 125–138.
[111] C. Tsai, C. Stewart, H. Tanenbaum, B. Roysam, Model-based method for improving
the accuracy and repeatability of estimating vascular bifurcations and crossovers from
retinal fundus images, IEEE Trans. Inf. Technol. Biomed. 8 (2) (2004) 122–130.
[112] T. Yedidya, R. Hartley, Tracking of blood vessels in retinal images using Kalman filter,
in: DICTA, 2008.
[113] K.S. Lin, C.L. Tsai, C.H. Tsai, M. Sofka, S.J. Chen, W.Y. Lin, Retinal vascular tree
reconstruction with anatomical realism, IEEE Trans. Biomed. Eng. 59 (12) (2012)
3337–3347.
[114] J. De, T. Ma, H. Li, M. Dash, L. Cheng, Automated tracing of retinal blood vessels
using graphical models, in: Scandinavian Conference on Image Analysis, 2013.
[115] J. De, H. Li, L. Cheng, Tracing retinal vessel trees by transductive inference, BMC
Bioinformatics 15 (20) (2014) 1–20.
[116] L. Cheng, J. De, X. Zhang, F. Lin, H. Li, Tracing retinal blood vessels by matrix-forest
theorem of directed graphs, in: MICCAI, 2014.
[117] J. De, L. Cheng, X. Zhang, F. Lin, H. Li, K. Ong, W. Yu, Y. Yu, S. Ahmed, A graph-
theoretical approach for tracing filamentary structures in neuronal and retinal images,
IEEE Trans. Med. Imaging 35 (1) (2016) 257–272.
[118] J. De, X. Zhang, F. Lin, L. Cheng, Transduction on directed graphs via absorbing
random walks, IEEE Trans. Pattern Anal. Mach. Intell. 40 (7) (2018) 1770–1784.
[119] Q. Lau, M. Lee, W. Hsu, T. Wong, Simultaneously identifying all true vessels from
segmented retinal images, IEEE Trans. Biomed. Eng. 60 (7) (2013) 1851–1858.
[120] X. Lyu, Q. Yang, S. Xia, S. Zhang, Construction of retinal vascular trees via curvature
orientation prior, in: IEEE International Conference on Bioinformatics and Biomedicine,
2016.
[121] E. Bekkers, R. Duits, T. Berendschot, B.M. ter Haar Romeny, A multi-orientation
analysis approach to retinal vessel tracking, J. Math. Imaging Vis. 49 (3) (2014)
583–610.
[122] E. Bekkers, R. Duits, A. Mashtakov, Y. Sachkov, Vessel tracking via sub-Riemannian
geodesics on the projective line bundle, in: International Conference on Geometric
Science of Information, 2017.
[123] E. Bekkers, D. Chen, J. Portegies, Nilpotent approximations of sub-Riemannian
distances for fast perceptual grouping of blood vessels in 2D and 3D, J. Math. Imaging
Vis. 60 (2018) 882–899.
[124] S. Abbasi-Sureshjani, M. Favali, G. Citti, A. Sarti, B.M. ter Haar Romeny, Curvature
integration in a 5D kernel for extracting vessel connections in retinal images, IEEE
Trans. Image Process. 27 (2) (2018) 606–621.
[125] J. Zhang, E. Bekkers, D. Chen, T. Berendschot, J. Schouten, J. Pluim, Y. Shi,
B. Dashtbozorg, B.M. ter Haar Romeny, Reconnection of interrupted curvilinear
structures via cortically inspired completion for ophthalmologic images, IEEE Trans.
Biomed. Eng. 65 (5) (2018) 1151–1165.
[126] C. Ventura, J. Pont-Tuset, S. Caelles, K. Maninis, L.V. Gool, Iterative deep retinal
topology extraction, in: International Workshop on Patch-Based Techniques in Medical
Imaging, 2018.