Retrospective Motion Compensation in Optical Coherence Tomography

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Optical coherence tomography (OCT) opens up the possibility to perform non-invasive, in vivo, micron scale 2D and 3D imaging of scattering tissue, such as the retina. Using 3D-OCT, quantitative measurements can be performed in ophthalmology, facilitating early detection and treatment of eye diseases, such as glaucoma and diabetic retinopathy. 3D-OCT datasets are not acquired instantaneously but are composed of many 1D axial scans recorded within few seconds. Thus, datasets show distortions and artefacts that result from motion of the eye during the scan. OCT images also contain speckle noise. We approach these problems by using multiple 3D scans of an area which are registered with each other to correct for motion and are combined so that speckle noise is reduced. We utilize the timing structure of the OCT imaging process, which determines the expected amount of motion between axial scans and therefore the distortion caused by motion. OCT images that were acquired with different scanning patterns are used to retrospectively estimate and compensate object motion. A novel software only registration method based on the optimization of a global, problem-specific objective function that is able to correct motion in all three dimensions is proposed. Combined with special post-processing for de-noising and image combination this approach offers great potential for achieving both more accurate data and improved image quality without the additional cost and complexity of hardware based motion correction methods. The ability to accurately and repeatably image the retina could improve the early, accurate diagnosis of disease and monitoring of treatment. The project transfers expertise in advanced registration and image enhancement to OCT imaging and aims to develop novel solutions to meet basic clinical needs.