Systems and methods to compensate for reflectance variation in OCT angiography

A method of compensating for the effect of tissue reflectance in optical coherence tomography (OCT) angiography, the method comprising:

• receiving a structural OCT dataset;
• obtaining an OCT decorrelation dataset;
• generating an en face angiogram from the OCT decorrelation dataset, the en face angiogram including a plurality of pixels;
• generating an en face reflectance image from the structural OCT dataset, the en face reflectance image including a plurality of pixels;
• for individual pixels in the en face reflectance image:
• calculating a dynamic threshold value based on the pixel's reflectance value;
• classifying a corresponding pixel in the en face angiogram as “flow,” provided that the pixel's decorrelation value is greater than the dynamic threshold value;
• classifying the corresponding pixel in the en face angiogram as “no flow,” provided that the pixel's decorrelation value is less than the dynamic threshold value;
• and
• returning a reflectance-compensated decorrelation image;
• wherein calculating a dynamic threshold value based on the pixel's reflectance value comprises using:
• Dt=(6.69×10−5)(S−Soffset)−0.035 [Minimum(S−Soffset)=787]
• where Dt is the decorrelation threshold, S is a decorrelation signal associated with the OCT decorrelation dataset, and Soffset is an offset value to account for the reflectance difference between regions used for compensation and a region where the dynamic threshold equation was derived.

A system comprising:

• an OCT system to acquire a structural optical coherence tomography (OCT) dataset and an OCT decorrelation dataset;
• a logic subsystem;
• and
• a data holding subsystem comprising machine-readable instructions stored thereon that are executable by the logic subsystem to:
• delineate a first retinal layer boundary, a second retinal layer boundary, and a third retinal layer boundary in the structural OCT dataset;
• generate an en face angiogram from the data between the first retinal layer boundary and the second retinal layer boundary in the OCT decorrelation dataset, the en face angiogram including a plurality of pixels;
• generate an en face reflectance image from the data between the second retinal layer boundary and the third retinal layer boundary in the structural OCT dataset, the en face reflectance image including a plurality of pixels;
• determine a dynamic threshold value for individual pixels in the en face reflectance image;
• classify the individual pixels as flow or no flow based on the respective dynamic threshold value;
• and
• generate a flow image based on the classified pixels.