1.Improvements at the hardware level
(1) Increase the scanning speed
Frequency domain OCT (FD-OCT) : Compared with time domain OCT (TD-OCT), FD-OCT has A faster scanning speed (up to tens of thousands to hundreds of thousands of A-scans per second), significantly reducing artifacts caused by patients’ minor movements (such as eye tremors and breathing).
Swept-frequency OCT (SS-OCT) : By rapidly tuning the laser light source to achieve high-speed scanning, it further shortens the single imaging time.
(2) Eye-tracking system
Real-time active tracking: In ophthalmic OCT, infrared cameras or pupil tracking technology (such as Zeiss’s Follow-Up Mode) are integrated to dynamically adjust the scanning position to compensate for eye movement.
Adaptive scanning: Adjust the scanning path based on real-time tracking data to avoid image shift caused by sudden movement of the patient.
(3) Probe stability design
Handheld OCT: For non-cooperative patients (such as children and Parkinson’s disease patients), lightweight probes or head fixation devices (such as jaw supports) are used.
Contact OCT: In intravascular OCT (IVOCT), the movement caused by heartbeats or breathing is reduced by touching the vessel wall through a catheter.
2. Correction of software algorithms
(1) Image Registration
Feature point matching: Align B-scan images from multiple scans using stable anatomical structures in the image (such as retinal vascular bifurcations).
Registration based on mutual information: Motion compensation is achieved by maximizing the similarity index between images (such as normalized mutual information).
(2) Motion detection and rejection
Abnormal frame detection: Identify invalid frames caused by intense movement (such as signal loss and distortion) and eliminate them during reconstruction.
Dynamic weighted average: Weights are assigned to images scanned multiple times (frames with smaller motion have higher weights), and the influence of random motion is reduced after fusion.
(3) Deep learning for artifact removal
Generative Adversarial networks (Gans) : Train models to restore clear structures from motion-degraded images (such as Artifact-Net).
Time series prediction model: Utilizing networks such as LSTM to predict eye movement trajectories and correct scanning positions in advance.
3. Optimization of operation processes
(1) Patient preparation
Fixed position: During ophthalmic examinations, use a head support and a forehead support, and remind the patient to avoid speaking or swallowing.
Shorten the time of a single scan: Prioritize small-area high-definition scanning (such as 5× 5mm instead of 12× 12mm) and complete large-area imaging in different regions.
Anesthesia or sedation: In animal experiments or pediatric examinations, surface anesthesia (such as in ophthalmology) or mild sedation may be used when necessary.
(2) Scanning strategy
Repeated scanning: Collect multiple sets of data from the same area and improve the signal-to-noise ratio through software fusion.
Orthogonal scanning: Scan the same area from a vertical direction (such as horizontal + vertical) to cross-verify the influence of motion.
(3) Real-time feedback
Operator monitoring: Observe real-time images during the scanning process. If motion artifacts are detected, immediately pause and re-scan.
Patient cooperation prompt: Guide the patient to remain stable through the gaze light or voice prompt (such as “Please gaze at the green light flashing”).
4. Solutions for special scenarios
Cardiovascular OCT (IVOCT)
Trigger the scan synchronously with the electrocardiogram (ECG), avoiding the cardiac pulsation period (collection during the diastolic period).
Use rapid withdrawal catheters (such as 20 mm/s) to reduce the impact of vascular displacement.
Intraoperative OCT
Combine the navigation system (such as neurosurgical robots) to update the scanning position in real time.
Non-contact probes are adopted to avoid interference from instruments.
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