In ophthalmology, navigation technology, often referred to as "eye-tracking," has been applied to various fields of eye care
FREMONT, CA: Technological advancements have substantially expanded their medicine and ophthalmology use. Smartphones and multipurpose devices are rapidly utilized for eye disease diagnosis, telemedicine, and self-monitoring. Deep learning and pattern recognition are two examples of how software technology has aided in the differentiation of abnormal images or results from normative databases in ophthalmic informatics.
Another remarkable example is motion-based navigation technology in both imaging and therapy of the eye. Numerous imaging instruments incorporate a real-time eye-tracking system, which aids in reducing motion artifacts and increases the signal-to-noise ratio during acquisition. These instruments include optical coherence tomography (OCT), microperimetry, and fluorescence and color imaging. In ophthalmic surgery, navigation was first used for laser vision correction, guided retinal photocoagulation, and intraocular lens (IOL) positioning guiding during cataract surgery. It has established itself as one of the most dependable technology representatives, transforming surgical interventions into safer, more standardized, and predictable operations with improved outcomes.
Navigation in surgery is characterized as "target location," "safe target reach," "current anatomic location," or "treatment accuracy evaluation." Apart from these critical orientation problems, surgical navigation is also employed as a measurement tool and information center, supplying surgeons with the appropriate information at the proper time.
When attempting to measure a specific structure of the eye precisely, ocular movements create an artifact that is difficult to "recalculate." As a result, eye movement compensation was applied to improve the reproducibility of these measurements.
One of the earliest uses was eye-tracking for laser Doppler velocimetry to assess ocular hemodynamics, where an eye-tracking system corrected eye movements and ensured an artifact-free image. This tracker is based on Purkinje pictures, which are infrared light reflections on the various surfaces of the eye. These changes in reflection resulting from the movement are analyzed and converted to eye movements. Later, Heidelberg retinal angiography was enhanced using an image-based eye tracker to adjust eye movements and improve image quality.
However, with OCT, a different type of correction is required to obtain high-resolution and motion artifact-free depth pictures. OCT tracking devices are classified as hardware-based or software-based. Hardware-based solutions incorporate additional hardware into the optical architecture of an instrument to capture other data for real-time or offline eye motion calculation. In software-based systems, motion patterns are estimated by comparing recorded data to a reference (OCT) image or making some prior assumptions about the nature of eye motion. By definition, hardware-based systems require software to calculate eye movements from the acquired data. The majority of the software applications are variants of cross-correlation-based picture registration algorithms.
Another sophisticated method for OCT eye tracking is picture distortion-based tracking. By evaluating distortions inside parts of each collected frame, a scanning laser ophthalmoscope (SLO) photographs the eye at a frame rate of 30 Hz but extracts eye movements at significantly greater rates. These recovered eye motion signals are converted to tracking signals and paired with the OCT galvo mirror driving signals.
OCT angiography (OCTA) is a novel technique for imaging the retinochoroidal vasculature, and minimizing motion artifacts using eye-tracking equipment is critical for reliable picture interpretation. Eye-tracking devices improve reproducibility and repeatability in the measurement of vascular flow, resulting in a significantly reduced quantity of motion artifacts, a substantially more vigorous signal intensity, and less variability in vessel density.