Three-dimensional choroidal vessel network quantification using swept source optical coherence tomography.

Area of Science:

• Ophthalmology
• Medical Imaging
• Biomedical Engineering

Background:

• Precise 3D segmentation of choroidal vessels is crucial for understanding ocular diseases like age-related macular degeneration and pathological myopia.
• Current methods may lack the precision needed for comprehensive analysis of the complex choroidal vasculature.

Purpose of the Study:

• To develop and validate a novel automatic framework for 3D choroidal vessel segmentation using SS-OCT data.
• To enable accurate visualization and quantification of three-dimensional choroidal vessel networks.

Main Methods:

• The framework delineates the retinal pigment epithelium (RPE) and extracts enface frames beneath it.
• Adaptive thresholding and segment propagation are used for initial and subsequent frame segmentation.
• Choroid boundary is determined using structural similarity index between adjacent frames.

Main Results:

• The framework was successfully tested on SS-OCT volumes from human and non-human primate subjects.
• Vessel metrics such as perfusion density, vessel density, and mean vessel diameter were computed.
• Demonstrated accurate 3D choroidal vessel segmentation.

Conclusions:

• The developed SS-OCT framework provides accurate 3D choroidal vessel segmentation.
• This technology can significantly aid clinicians in quantifying blood perfusion for improved diagnosis and management of retinal diseases.