Quantitative evaluation of image registration techniques in the case of retinal images

被引:8
|
作者
Gavet, Yann [1 ]
Fernandes, Mathieu [1 ]
Pinoli, Jean-Charles [1 ]
机构
[1] Ecole Natl Super Mines, CIS LPMG CNRS, F-42023 St Etienne, France
关键词
VESSEL SEGMENTATION;
D O I
10.1117/1.JEI.21.2.021118
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In human retina observation (with non mydriatic optical microscopes), an image registration process is often employed to enlarge the field of view. Analyzing all the images takes a lot of time. Numerous techniques have been proposed to perform the registration process. Its good evaluation is a difficult question that is then raising. This article presents the use of two quantitative criterions to evaluate and compare some classical feature-based image registration techniques. The images are first segmented and the resulting binary images are then registered. The good quality of the registration process is evaluated with a normalized criterion based on the. dissimilarity criterion, and the figure of merit criterion (fom), for 25 pairs of images with a manual selection of control points. These criterions are normalized by the results of the affine method (considered as the most simple method). Then, for each pair, the influence of the number of points used to perform the registration is evaluated. (C) 2012 SPIE and IS&T. [DOI: 10.1117/1.JEI.21.2.021118]
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Automatic quantitative evaluation of image registration techniques with the ε dissimilarity criterion in the case of retinal images
    Gavet, Yann
    Fernandes, Mathieu
    Pinoli, Jean-Charles
    TENTH INTERNATIONAL CONFERENCE ON QUALITY CONTROL BY ARTIFICIAL VISION, 2011, 8000
  • [2] Techniques for temporal registration of retinal images
    Fang, B
    Hsu, W
    Lee, ML
    ICIP: 2004 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1- 5, 2004, : 1089 - 1092
  • [3] An automated, quantitative, and case-specific evaluation of deformable image registration in computed tomography images
    Kierkels, R. G. J.
    den Otter, L. A.
    Korevaar, E. W.
    Langendijk, J. A.
    van der Schaaf, A.
    Knopf, A. C.
    Sijtsema, N. M.
    PHYSICS IN MEDICINE AND BIOLOGY, 2018, 63 (04):
  • [4] A quantitative evaluation of deformable image registration based on Halcyon MVCBCT images
    Huang, Y.
    Wu, H.
    Wang, W.
    Zhang, Y.
    RADIOTHERAPY AND ONCOLOGY, 2020, 152 : S891 - S891
  • [5] Quantitative and Qualitative Evaluation of Selected Lung MR Image Registration Techniques
    Wujcicki, Artur
    Materka, Andrzej
    COMPUTER VISION AND GRAPHICS, ICCVG 2014, 2014, 8671 : 653 - 660
  • [6] Evaluation of Effectiveness of Image Enhancement Techniques with Application to Retinal Fundus images
    Pal, Mahua Nandy
    Banerjee, Minakshi
    2020 4TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND NETWORKS (CINE 2020), 2020,
  • [7] Registration and fusion of retinal images -: An evaluation study
    Laliberté, F
    Gagnon, L
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2003, 22 (05) : 661 - 673
  • [8] Quantitative evaluation of deformable image registration
    Zhong, Hualiang
    Siebers, Jeffrey V.
    2007 4TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING : MACRO TO NANO, VOLS 1-3, 2007, : 724 - 727
  • [9] An Automatic Evaluation Method for Retinal Image Registration
    Shu, Yifan
    Kang, Jieliang
    Li, Huiqi
    Xu, Jie
    Xu, Liang
    PROCEEDINGS OF THE 2017 12TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2017, : 75 - 79
  • [10] A Comparative Study on Image Registration Techniques for SAR Images
    Sreeja, G.
    Saraniya, O.
    2019 5TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING & COMMUNICATION SYSTEMS (ICACCS), 2019, : 947 - 953