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Registration of Fluorescein Angiography and Optical Coherence Tomography Images of Curved Retina Via Scanning Laser Ophthalmoscopy Photographs Publisher



Almasi R1 ; Vafaei A1 ; Ghasemi Z2 ; Ommani MR3 ; Dehghani AR3, 4 ; Rabbani H5
Authors
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Authors Affiliations
  1. 1. Department of Computer Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran
  2. 2. Department of Electrical and Computer Engineering, University of Detroit Mercy, Detroit, 48202, MI, United States
  3. 3. Didavaran Eye Clinic, Isfahan, Iran
  4. 4. Department of Ophthalmology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
  5. 5. Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Biomedical Optics Express Published:2020


Abstract

Accurate and automatic registration of multimodal retinal images such as fluorescein angiography (FA) and optical coherence tomography (OCT) enables utilization of supplementary information. FA is a gold standard imaging modality that depicts neurovascular structure of retina and is used for diagnosing neurovascular-related diseases such as diabetic retinopathy (DR). Unlike FA, OCT is non-invasive retinal imaging modality that provides cross-sectional data of retina. Due to differences in contrast, resolution and brightness of multimodal retinal images, the images resulted from vessel extraction of image pairs are not exactly the same. Also, prevalent feature detection, extraction and matching schemes do not result in perfect matches. In addition, the relationships between retinal image pairs are usually modeled by affine transformation, which cannot generate accurate alignments due to the non-planar retina surface. In this paper, a precise registration scheme is proposed to align FA and OCT images via scanning laser ophthalmoscopy (SLO) photographs as intermediate images. For this purpose, first a retinal vessel segmentation is applied to extract main blood vessels from the FA and SLO images. Next, a novel global registration is proposed based on the Gaussian model for curved surface of retina. For doing so, first a global rigid transformation is applied to FA vessel-map image using a new feature-based method to align it with SLO vessel-map photograph, in a way that outlier matched features resulted from not-perfect vessel segmentation are completely eliminated. After that, the transformed image is globally registered again considering Gaussian model for curved surface of retina to improve the precision of the previous step. Eventually a local non-rigid transformation is exploited to register two images perfectly. The experimental results indicate the presented scheme is more precise compared to other registration methods. © 2020 Optical Society of America.
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