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V. Mani, Dr.S. rivazhagan (2013)
Survey of Medical Image Registration, 1
R. Karani, T. Sarode (2012)
Image Registration using Discrete Cosine Transform and Normalized Cross Correlation
G. Yang, C. Stewart, M. Sofka, Chia-Ling Tsai (2007)
Registration of Challenging Image Pairs: Initialization, Estimation, and DecisionIEEE Transactions on Pattern Analysis and Machine Intelligence, 29
Dong Ni, Y. Qu, Xuan Yang, Yim-Pan Chui, T. Wong, Simon Ho, P. Heng (2008)
Volumetric Ultrasound Panorama Based on 3D SIFTMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 11 Pt 2
B. Zitová, J. Flusser (2003)
Image registration methods: a surveyImage Vis. Comput., 21
Gang Wang, Zhicheng Wang, Yufei Chen, W. Zhao (2015)
Robust point matching method for multimodal retinal image registrationBiomed. Signal Process. Control., 19
Jun Zhu, Mingwu Ren (2014)
Image Mosaic Method Based on SIFT Features of Line SegmentComputational and Mathematical Methods in Medicine, 2014
(2007)
initialization, estimation, and decision,” IEEE Trans
C. Archibald, P. Kwok (1995)
Research in Computer and Robot Vision
S. Patankar, J. Kulkarni (2015)
Orthogonal moments for determining correspondence between vessel bifurcations for retinal image registrationComputer methods and programs in biomedicine, 119 3
J. Staal, M. Abràmoff, M. Niemeijer, M. Viergever, B. Ginneken (2004)
Ridge-based vessel segmentation in color images of the retinaIEEE Transactions on Medical Imaging, 23
(2013)
Special Issue on Voronoi Diagrams and Their Applications, Vol
Carlos Hernandez-Matas, Xenophon Zabulis, A. Triantafyllou, P. Anyfanti, S. Douma, Antonis Argyros (2017)
FIRE: Fundus Image Registration dataset, 1
A. Laraqui, A. Baataoui, A. Saaidi, A. Jarrar, Mohamed Masrar, K. Satori (2016)
Image mosaicing using voronoi diagramMultimedia Tools and Applications, 76
D. Lowe (2004)
Distinctive Image Features from Scale-Invariant KeypointsInternational Journal of Computer Vision, 60
A. Vedaldi, B. Fulkerson (2010)
Vlfeat: an open and portable library of computer vision algorithmsProceedings of the 18th ACM international conference on Multimedia
Bernhard Wrobel (2001)
Multiple View Geometry in Computer VisionKünstliche Intell., 15
T. Chanwimaluang, Guoliang Fan, S. Fransen (2006)
Hybrid retinal image registrationIEEE Transactions on Information Technology in Biomedicine, 10
Carlos Hernandez-Matas, Antonis Argyros, Xenophon Zabulis (2019)
Retinal image preprocessing, enhancement, and registrationComputational Retinal Image Analysis
Sajib Saha, D. Xiao, Shaun Frost, Y. Kanagasingam (2016)
A Two-Step Approach for Longitudinal Registration of Retinal ImagesJournal of Medical Systems, 40
Y. Dobashi, T. Haga, H. Johan, T. Nishita (2002)
A Method for Creating Mosaic Images Using Voronoi Diagrams
Carlos Hernandez-Matas, Xenophon Zabulis, Antonis Argyros (2017)
An experimental evaluation of the accuracy of keypoints-based retinal image registration2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
(1991)
An introductory tutorial on kd trees
Kun Zhang, Encai Zhang, Jichun Li, Guannan Chen (2016)
Retinal image automatic registration based on local bifurcation structure2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
Carlos Hernandez-Matas, Xenophon Zabulis, Antonis Argyros (2016)
Retinal image registration through simultaneous camera pose and eye shape estimation2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Lei Zhang, Mark Fisher, Wenjia Wang (2015)
Retinal vessel segmentation using multi-scale textons derived from keypointsComputerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 45
R. Bolles, M. Fischler (1981)
A RANSAC-Based Approach to Model Fitting and Its Application to Finding Cylinders in Range Data
Li Chen, Xiaotong Huang, Jing Tian (2015)
Retinal image registration using topological vascular tree segmentation and bifurcation structuresBiomed. Signal Process. Control., 16
J. Jan, J. Odstrcilík, J. Gazárek, R. Kolář (2012)
Retinal image analysis aimed at blood vessel tree segmentation and early detection of neural-layer deteriorationComputerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 36 6
C. Patel, T. Fung, M. Muqit, D. Mordant, J. Brett, L. Smith, E. Adams (2013)
Non-contact ultra-widefield imaging of retinopathy of prematurity using the Optos dual wavelength scanning laser ophthalmoscopeEye, 27
Chunming Tang, Yancheng Dong, Xiaohong Su (2008)
Automatic Registration Based on Improved SIFT for Medical Microscopic Sequence Images2008 Second International Symposium on Intelligent Information Technology Application, 1
(2003)
a survey,” Image
D. Toslak, D. Thapa, Yanjun Chen, M. Erol, V. R., Paul Chan, Xincheng Yao (2016)
Trans-palpebral illumination: an approach for wide-angle fundus photography without the need for pupil dilation.Optics letters, 41 12
R. Ramli, M. Idris, K. Hasikin, N. Karim, A. Wahab, I. Ahmedy, F. Ahmedy, N. Kadri, H. Arof (2017)
Feature-Based Retinal Image Registration Using D-Saddle FeatureJournal of Healthcare Engineering, 2017
Jalil Jalili received his master's degree from Isfahan Medical Sciences University and his doctorate degree from Tehran University of Medical Sciences (TUMS)
Chengyin Liu, Jiayi Ma, Yong Ma, Jun Huang (2016)
Retinal image registration via feature-guided Gaussian mixture model.Journal of the Optical Society of America. A, Optics, image science, and vision, 33 7
Carlos Hernandez-Matas, Xenophon Zabulis, Antonis Argyros (2015)
Retinal image registration based on keypoint correspondences, spherical eye modeling and camera pose estimation2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Ben Shen, Dongbo Zhang, Yinghui Peng (2012)
Blood Bifurcation Structure and Global to Local Strategy Based Retinal Image Registration
R. Szeliski, M. Uyttendaele, Drew Steedly (2011)
Fast Poisson blending using multi-splines2011 IEEE International Conference on Computational Photography (ICCP)
A. Perez-Rovira, R. Cabido, E. Trucco, S. McKenna, J. Hubschman (2012)
RERBEE: Robust Efficient Registration via Bifurcations and Elongated Elements Applied to Retinal Fluorescein Angiogram SequencesIEEE Transactions on Medical Imaging, 31
(2006)
The matching method based on RANSAC algorithm for estimation of the fundamental matrix
A. Cideciyan (1995)
Registration of ocular fundus images: an algorithm using cross-correlation of triple invariant image descriptorsIEEE Engineering in Medicine and Biology Magazine, 14
Qiao Hu, M. Abràmoff, M. Garvin (2015)
Automated construction of arterial and venous trees in retinal imagesJournal of Medical Imaging, 2
A. Condurache, A. Mertins (2012)
Segmentation of retinal vessels with a hysteresis binary-classification paradigmComputerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 36 4
H. Bay, Andreas Ess, T. Tuytelaars, L. Gool (2008)
Speeded-Up Robust Features (SURF)Comput. Vis. Image Underst., 110
J. Sole, Yu Huang, J. Llach (2007)
Mosaic-based figure-ground segmentation along with static segmentation by mean shift
Hamid Bazargani, O. Bilaniuk, R. Laganière (2018)
A fast and robust homography scheme for real-time planar target detectionJournal of Real-Time Image Processing, 15
E. Ong, J. Lee, Jun Cheng, Guozhen Xu, B. Lee, A. Laude, S. Teoh, T. Lim, D. Wong, Jiang Liu (2015)
A Robust Outlier Elimination Approach for Multimodal Retina Image Registration
Abstract.Purpose: Peripheral retinal lesions substantially increase the risk of diabetic retinopathy and retinopathy of prematurity. The peripheral changes can be visualized in wide field imaging, which is obtained by combining multiple images with an overlapping field of view using mosaicking methods. However, a robust and accurate registration of mosaicking techniques for normal angle fundus cameras is still a challenge due to the random selection of matching points and execution time. We propose a method of retinal image mosaicking based on scale-invariant feature transformation (SIFT) feature descriptor and Voronoi diagram.Approach: In our method, the SIFT algorithm is used to describe local features in the input images. Then the input images are subdivided into regions based on the Voronoi method. Each pair of Voronoi regions is matched by the method zero mean normalized cross correlation. After matching, the retinal images are mapped into the same coordinate system to form a mosaic image. The success rate and the mean registration error (RE) of our method were compared with those of other state-of-the-art methods for the P category of the fundus image registration database.Results: Experimental results show that the proposed method accurately registered 42% of retinal image pairs with a mean RE of 3.040 pixels, while a lower success rate was observed in the other four state-of-the-art retinal image registration methods GDB-ICP (33%), Harris-PIIFD (0%), HM-2016 (0%), and HM-2017 (2%).Conclusions: The proposed method outperforms state-of-the-art methods in terms of quality and running time and reduces the computational complexity.
Journal of Medical Imaging – SPIE
Published: Jul 1, 2020
Keywords: retinal image mosaicking; scale-invariant feature transformation feature descriptor; Voronoi diagram; database; fundus image
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