Retinal Vessel Detection

Retinal Vessel Detection detects and analyzes blood vessel networks in retinal images to generate vessel maps for ophthalmic diagnosis and monitoring.

Key Features:

• Gabor Transform: Extracts multi-scale and multi-directional features from retinal images to capture vessel texture and structural details.
• Machine Learning (Generalized Linear Model, GLM): Classifies image regions as vessel or non-vessel using features derived from the Gabor transform.

Scientific Applications:

• Ophthalmology: Provides retinal vessel maps to support clinical assessment and monitoring of retinal vascular health.
• Diabetic retinopathy: Assists detection and quantification of vascular changes associated with diabetic retinopathy.
• Glaucoma and age-related macular degeneration: Aids assessment of vascular features relevant to glaucoma and age-related macular degeneration.

Methodology:

Extract multi-scale, multi-directional features using the Gabor transform and classify regions as vessel or non-vessel with a Generalized Linear Model (GLM).