Abstract
Optical coherence tomography enables high-resolution 3D imaging of retinal layers in the human eye. The thickness of the layers is commonly assessed to understand a variety of retinal and systemic disorders. Yet, the thickness data are complex and currently need to be considerably reduced prior to further processing and analysis. This leads to a loss of information on localized variations in thickness, which is important for early detection of certain retinal diseases. We propose an enhanced grid-based reduction and exploration of retinal thickness data. Alternative grids are computed, their representation quality is rated, and best fitting grids for given thickness data are suggested. Selected grids are then visualized, adapted, and compared at different levels of granularity. A visual analysis tool bundles all computational, visual, and interactive means in a flexible user interface. We demonstrate the utility of our tool in a complementary analysis procedure, which eases the evaluation of ophthalmic study data. Ophthalmologists successfully applied our solution to study localized variations in thickness of retinal layers in patients with diabetes mellitus.
Highlights
Optical coherence tomography (OCT) [1] is a widely-used noninvasive technique to capture high-resolution 3D images of retinal substructures
The thickness data are complex and currently need to be considerably reduced prior to further processing and analysis. This leads to a loss of information on localized variations in thickness, which is important for early detection of certain retinal diseases
Evaluation of ophthalmic studies: We apply our tool to investigate localized variations in retinal layer thickness in two cross-sectional studies with patients suffering from diabetes mellitus
Summary
Optical coherence tomography (OCT) [1] is a widely-used noninvasive technique to capture high-resolution 3D images of retinal substructures. Established reduction methods for retinal thickness data are based on retinal grids These grids are used to spatially divide the retina into few large regions and to derive aggregated thickness measures for each region. This helps to get a quick overview of the layers’ thickness in anatomically predefined areas. We aim at supporting ophthalmologists in their grid-based visual analysis of retinal layer thickness. We propose an enhanced data reduction scheme together with a visual analysis tool for the exploration of alternative grids. We integrate our enhanced grid design and exploration in a flexible visual analysis tool and describe how an associated analysis procedure helped ophthalmologists to evaluate data of two ophthalmic studies.
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