Open AccessIterative registration for multi‐modality retinal fundus photographs using directional vessel skeleton
Author(s) -
Kong Wenwen,
Zang Pengxiao,
Niu Sijie,
Li Dengwang
Publication year - 2021
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/ipr2.12054
Subject(s) - fundus (uterus) , artificial intelligence , computer vision , computer science , image registration , retinal , optical coherence tomography , medicine , ophthalmology , image (mathematics)
This paper proposes an automated registration method for multi‐modality retinal fundus photographs based on the directional vessel skeleton. The main purpose is to register two retinal fundus photographs with different modalities of the same scanning region, which can provide multi‐modality information for clinicians to diagnose retinal diseases or to make a treatment decision. The directional vessel skeleton of each fundus image is first detected by bias field correction and Gabor filter. The final registered fundus photographs are then obtained by the iterative affine registration between the detected directional vessel skeletons of two photographs. In this work, four kinds of fundus photographs in the macular regions of the patient with diseases, consisting of 20 optical coherence tomography fundus images, 20 colour fundus photographs, 20 fluorescein fundus angiography images and 20 indocyanine green angiography images, are utilised to quantitatively evaluate the proposed method. The root‐mean‐square errors show an advantageous performance in both registration success rate and accuracy.