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Image-guidance in ophthalmic surgery using optical coherence tomography

dc.creatorEl-Haddad, Mohamed T.
dc.description.abstractOphthalmic surgery involves manipulation of layered tissue structures on milli- to micrometer scales. Traditional surgical microscopes provide a two-dimensional view of the surgical field with limited depth perception which precludes accurate depth-resolved visualization of surgically-induced tissue morphology. Optical coherence tomography (OCT) enables non-contact exogenous contrast-free imaging of subsurface tissue microstructures, and is currently the gold standard for ophthalmic clinical diagnostics. Over the last decade, translation of OCT technologies to applications in surgical planning and guidance in ophthalmology has been an active area of research and commercialization. Clinical studies confirmed benefits of intraoperative OCT including verification that surgical goals have been achieved; improved axial resolution, contrast, and visualization of subsurface features-of-interested as compared to surgical stereomicroscopy; and image-guided surgical maneuvers, especially during minimally invasive and microsurgical procedures. However, several barriers still exist that limit large-scale adoption of intraoperative OCT. These include complex alignment of the OCT field-of-view (FOV) with that of the surgical microscope; shadowing artefacts that limit or completely preclude tissue visualization below the surgical instrument shaft; the fixed OCT FOV which impedes continuous visualization of instrument-tissue interactions; and the inherent trade-offs between FOV, acquisition speed, and sampling density that limit real-time imaging of surgical dynamics. This dissertation describes systems, methods, and enabling technologies to address the aforementioned limitations through the development of a novel microscope-intraoperative OCT platform, with integrated and automated real-time tracking of surgical instruments for continuous visualization of instrument-tissue interactions. The outlined work addresses critical barriers to clinical adoption of intraoperative OCT. Automated tracking will provide enhanced ergonomics by eliminating the need for manual alignment of the OCT FOV with the surgical region-of-interest (ROI). Additionally, using commercially available high-speed sources and detectors, more sophisticated visualizations will be possible such as tracked video-rate volumes around the instrument shaft, and real-time spatial interpolation for suppression of shadowing artefacts and visualization of depth-resolved cross-sections of the surgical dynamics. Finally, this will enable automated extraction of quantitative information during surgery which may facilitate analysis and prediction of visual outcomes based on surgical intervention, development of novel surgical maneuvers that were not previously possible, and integration with robotic-surgery platforms.
dc.subjectComputer vision
dc.subjectconfocal microscopy
dc.subjectoptical coherence tomography
dc.subjectstereo vision
dc.subjectobject detection
dc.subjectmachine learning
dc.titleImage-guidance in ophthalmic surgery using optical coherence tomography
dc.contributor.committeeMemberBenoit Dawant
dc.contributor.committeeMemberKaren Joos
dc.contributor.committeeMemberRichard Alan Peters
dc.contributor.committeeMemberAndrew Rollins
dc.contributor.committeeMemberMichael Miga
dc.type.materialtext Engineering University
dc.contributor.committeeChairYuankai Tao

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