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3D Retinal Vessel Density Mapping With OCT-Angiography
- Source :
- IEEE J Biomed Health Inform
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- Optical Coherence Tomography Angiography (OCTA) is a novel, non-invasive imaging modality of retinal capillaries at micron resolution. Recent studies have correlated macular OCTA vascular measures with retinal disease severity and supported their use as a diagnostic tool. However, these measurements mostly rely on a few summary statistics in retinal layers or regions of interest in the two-dimensional (2D) en face projection images. To enable 3D and localized comparisons of retinal vasculature between longitudinal scans and across populations, we develop a novel approach for mapping retinal vessel density from OCTA images. We first obtain a high-quality 3D representation of OCTA-based vessel networks via curvelet-based denoising and optimally oriented flux (OOF). Then, an effective 3D retinal vessel density mapping method is proposed. In this framework, a vessel density image (VDI) is constructed by diffusing the vessel mask derived from OOF-based analysis to the entire image volume. Subsequently, we utilize a non-linear, 3D OCT image registration method to provide localized comparisons of retinal vasculature across subjects. In our experimental results, we demonstrate an application of our method for longitudinal qualitative analysis of two pathological subjects with edema during the course of clinical care. Additionally, we quantitatively validate our method on synthetic data with simulated capillary dropout, a dataset obtained from a normal control (NC) population divided into two age groups and a dataset obtained from patients with diabetic retinopathy (DR). Our results show that we can successfully detect localized vascular changes caused by simulated capillary loss, normal aging, and DR pathology even in presence of edema. These results demonstrate the potential of the proposed framework in localized detection of microvascular changes and monitoring retinal disease progression.
- Subjects :
- Population
Image registration
Article
030218 nuclear medicine & medical imaging
03 medical and health sciences
chemistry.chemical_compound
Imaging, Three-Dimensional
0302 clinical medicine
Health Information Management
Image Interpretation, Computer-Assisted
Curvelet
medicine
Humans
Electrical and Electronic Engineering
education
Projection (set theory)
education.field_of_study
Retina
Diabetic Retinopathy
business.industry
Angiography
Retinal Vessels
Retinal
Diabetic retinopathy
medicine.disease
Computer Science Applications
Retinal vessel
medicine.anatomical_structure
chemistry
030221 ophthalmology & optometry
business
Tomography, Optical Coherence
Biotechnology
Biomedical engineering
Subjects
Details
- ISSN :
- 21682208 and 21682194
- Volume :
- 24
- Database :
- OpenAIRE
- Journal :
- IEEE Journal of Biomedical and Health Informatics
- Accession number :
- edsair.doi.dedup.....4834754ffe1379daecd2c9f2a8339f06