ThicknessTool

ThicknessTool measures retinal nuclear layer thickness in digital images for the ImageJ platform to quantify outer nuclear layer (ONL) and inner nuclear layer (INL) thickness and the ONL/INL ratio.

Key Features:

• Automated Measurement: Performs automated thickness measurements by following the contour of the retina in digital images.
• Calibration and Accuracy: Calibrated using mock binary skeletonized mask images with varying thicknesses and rotations, yielding an overall coefficient of variation of 0.00% in the calibration dataset.
• Training and Validation: Training on immunofluorescence retinal nuclear layer images showed no significant differences between ThicknessTool and manual observers for ONL, INL, and ONL/INL ratio, with lower measurement bias than inter-observer variability.
• Performance in Validation: Validated on a retinal detachment image dataset where ThicknessTool detected ONL thinning with statistical significance (p = 0.006), compared to non-significant manual measurements (p = 0.069).

Scientific Applications:

• Retinal Research: Quantifies layer-specific morphological changes in studies of retinal detachment and degenerative retinal conditions.
• Clinical Diagnostics: Detects subtle changes in ONL and INL thickness that can inform diagnosis and monitoring of retinal pathologies.

Methodology:

Calibration with mock binary skeletonized mask images of known thicknesses and rotations; automated contour-following measurement of retinal nuclear layers in digital images; training by comparing automated measurements to manual observers on immunofluorescence retinal images; validation on a retinal detachment image dataset.