Abstract
Complex differential variance (CDV) provides phase-sensitive angiographic imaging for optical coherence tomography (OCT) with immunity to phase-instabilities of the imaging system and small-scale axial bulk motion. However, like all angiographic methods, measurement noise can result in erroneous indications of blood flow that confuse the interpretation of angiographic images. In this paper, a modified CDV algorithm that corrects for this noise-bias is presented. This is achieved by normalizing the CDV signal by analytically derived upper and lower limits. The noise-bias corrected CDV algorithm was implemented into an experimental 1 μm wavelength OCT system for retinal imaging that used an eye tracking scanner laser ophthalmoscope at 815 nm for compensation of lateral eye motions. The noise-bias correction improved the CDV imaging of the blood flow in tissue layers with a low signal-to-noise ratio and suppressed false indications of blood flow outside the tissue. In addition, the CDV signal normalization suppressed noise induced by galvanometer scanning errors and small-scale lateral motion. High quality cross-section and motion-corrected en face angiograms of the retina and choroid are presented.
Highlights
Angiography has become one of the primary imaging modes of optical coherence tomography (OCT) [1,2]
Complex differential variance (CDV) angiography imaging was performed on a healthy volunteer in the macula using the wide-field imaging protocol
The severity of the noise is not uniform throughout the image, which makes the application of a simple threshold difficult
Summary
Angiography has become one of the primary imaging modes of optical coherence tomography (OCT) [1,2]. Because the phase signal in OCT is sensitive to instrument synchronization and timing errors, small axial displacements of the sample, and mechanical motion or vibrations, phase-based angiography has required methods to phase stabilize the measurements. These include optical clocking and triggering of the wavelength-swept laser and signal digitization [21,22] as well as post-processing methods that rely on a reference (mirror) signal for numerical phase correction of digitization errors [23,24,25]. Stable galvanometer scanning patterns have been developed to minimize vibrations and positioning errors [18,26], while sample bulk motion is often numerically compensated with phase changes measured from stationary tissues [4,16]
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