Mohamed Tarek El-Haddad, Ph.D.
Research Scientist, Facebook Reality Labs
Ivan Bozic, M.S.
Ph.D. Candidate, Department of Biomedical Engineering, Tulane University
NSF Graduate Research Fellow, Department of Biomedical Engineering, Columbia University
Graduate Student, Department of Biomedical Engineering, Texas A&M University
Graduate Student, Department of Electrical and Computer Engineering, The Ohio State University
Graduate Student, Department of Biomedical Engineering, Duke University
Multimodality ophthalmic imaging technologies
Non-invasive biological imaging is crucial for understanding in vivo structure and function. Optical coherence tomography (OCT) and reflectance confocal microscopy are two of the most widely used optical modalities for exogenous contrast-free high-resolution three-dimensional imaging in non-fluorescent scattering tissues. However, sample motion remains a critical barrier to raster-scanned acquisition and reconstruction of wide-field anatomically accurate volumetric datasets. We introduce spectrally encoded coherence tomography and reflectometry (SECTR), a high-speed multimodality system for simultaneous OCT and spectrally-encoded reflectance (SER) imaging. SECTR utilizes a robust system design consisting of shared optical relays, scanning mirrors, swept-laser, and digitizer to achieve the fastest reported in vivo multimodal imaging rate of 2 gigapixels-per-second. Our optical design and acquisition scheme enable spatiotemporally co-registered acquisition of OCT cross-sections simultaneously with en face SER images for multi-volumetric mosaicking. Complementary axial and lateral translation and rotation are extracted from OCT and SER data, respectively, for full volumetric estimation of sample motion with micron spatial and millisecond temporal resolution.
Intraoperative imaging for ophthalmic surgical guidance
Translation of optical coherence tomography (OCT) technologies for intraoperative visualization enables in vivo micron-resolution imaging of subsurface tissue structures and image-guided clinical decision-making. Over the last decade, intraoperative OCT has evolved from two-dimensional imaging using handheld probes to include stereomicroscope integrated systems that provide real-time three- and four-dimensional visualization of surgical maneuvers. We have developed multimodal spectrally encoded coherence tomography and reflectometry (SECTR) technologies that allow for simultaneous and intrinsically co-registered en face spectrally encoded reflectance (SER) and cross-sectional OCT imaging. We also recently demonstrated an intraoperative SECTR (iSECTR) microscope-integrated scan-head and ex vivo and in vivo video-rate volumetric (4D) imaging at 18 volumes-per-second. SECTR overcomes the FOV and imaging speed trade-offs of current-generation ophthalmic iOCT by providing complementary en face spatial information to enable real-time image aiming, retinal tracking, bulk-motion compensation, and multi-volumetric averaging and mosaicking. We are actively working to develop novel technologies, feedback mechanisms, and maneuvers that integrate volumetric iSECTR data for image-guided ophthalmic surgery.
Machine-learning assisted imaging of surgical dynamics
Intraoperative optical coherence tomography (iOCT) enables volumetric imaging of surgical maneuvers. However, the lack of automated instrument-tracking remains a critical barrier to real-time surgical feedback and iOCT-guided surgery. We previously presented spectrally-encoded coherence tomography and reflectometry (SECTR), which provides simultaneous imaging of spatiotemporally co-registered orthogonal imaging planes at several gigapixels-per-second. Here, we demonstrate automated surgical instrument-tracking and adaptive-sampling of OCT using a combination of deep-learning and SECTR. We believe this method overcomes critical barriers to clinical translation of iOCT and offers several computational and system advantages over previous approaches.
Point-of-care ophthalmic diagnostic imaging
Optical coherence tomography (OCT) is the gold standard for quantitative ophthalmic imaging. The majority of commercial and research systems require patients to fixate and be imaged in a seated upright position, which limits the ability to perform ophthalmic imaging in bedridden or pediatric patients. Handheld OCT devices overcome this limitation, but image quality often suffers due to a lack of real-time aiming and patient eye and photographer motion. Here, we describe a handheld spectrally encoded coherence tomography and reflectometry (SECTR) system that enables simultaneous en face reflectance and cross-sectional OCT imaging. The handheld probe utilizes a custom double-pass scan lens for fully telecentric OCT scanning with a compact optomechanical design and a rapid-prototyped enclosure to reduce overall system size and weight. We also introduce a novel variable velocity scan waveform that allows for simultaneous acquisition of densely-sampled OCT angiography (OCTA) volumes and widefield reflectance images, which enables high-resolution vascular imaging with precision motion-tracking for volumetric motion-correction and multi-volumetric mosaicking. Finally, we demonstrate in vivo human retinal OCT and OCT angiography (OCTA) imaging using handheld SECTR on a healthy volunteer. Clinical translation of handheld SECTR will allow for high-speed, motion-corrected widefield OCT and OCTA imaging in bedridden and pediatric patients that may benefit ophthalmic disease diagnosis and monitoring.
Structural and functional imaging in rodent models of ophthalmic injury and repair
Rodent models are robust tools for understanding human retinal disease and function because of their similarities with human physiology and anatomy and availability of genetic mutants. Optical coherence tomography (OCT) has been well-established for ophthalmic imaging in rodents and enables depth-resolved visualization of structures and image-based surrogate biomarkers of disease. Similarly, fluorescence confocal scanning laser ophthalmoscopy (cSLO) has demonstrated utility for imaging endogenous and exogenous fluorescence and scattering contrast in the mouse retina.
Collaborators: Edward Levine, Ph.D.
Quantitative vascular imaging
Quantitative measurements of lung microvessels would benefit characterization of vascular function and remodeling in pulmonary vascular diseases. Here, we present a novel method for quantitative measurements of lung vasculature using multi-volumetric optical coherence microscopy (OCM). Murine lungs were perfused with scattering contrast, fixed, and optically cleared. OCM volumes were acquired and segmented in post-processing to quantify vessel diameters. This proof-of-concept demonstrates the utility of our OCM and tissue preparation approach, which can be extended to compare microvasculature changes in entire lung lobes in animal models of pulmonary disease.
Collaborators: Susan Majka, Ph.D.
DIIGI Lab publishes work on non-contact optical metrology
Recent graduate Dr. El-Haddad publishes his work on non-contact characterization of compound optical elements in Scientific Reports. The method characterizes compound optical elements including curvatures, material and air-gap thicknesses, and glass types using a combination of reflectance confocal microscopy, low-coherence interferometry, and computational ray-tracing. Congrats Mohamed! [Link]
Incoming graduate student joins DIIGI Lab
Morgan Ringel graduated Duke University in 2018 with a B.S.E. in Biomedical Engineering and Electrical & Computer Engineering and will be starting as a first-year graduate student in the Department of Biomedical Engineering. Welcome Morgan! [Link]
Incoming graduate student joins DIIGI Lab
Rachel Eimen graduated Clemson University in 2019 with a B.S. in Computer Engineering and will be starting as a first-year graduate student in the Department of Biomedical Engineering. Welcome Rachel! [Link]
DIIGI Lab publishes work on handheld ophthalmic imaging technologies
Graduate student Joe Malone publishes his work on handheld spectrally encoded coherence tomography and reflectometry (SECTR) in Neurophotonics. SECTR is a multimodality ophthalmic imaging technology that combines optical coherence tomography and spectrally encoded reflectance imaging to enable volumetric motion-correction and multi-volumetric mosaicking. Congrats Joe! [Link]
DIIGI Lab and MedICL Lab receive 2019 Discovery Grant
Office of the Provost will fund a collaboration between DIIGI and MedICL Labs to develop novel point-of-care technologies to diagnose retinal disease in premature infants. This project will be a collaboration between Co-PIs Prof. Kenny Tao (Department of Biomedical Engineering) and Prof. Ipek Oguz (Computer Science and Computer Engineering) at Vanderbilt University and ophthalmologists Dr. Anthony Daniels and Dr. Irina De la Huerta (Vanderbilt Eye Institute) at Vanderbilt University Medical Center. [Link]
DIIGI Lab hoods first graduate student
Mohamed El-Haddad was hooded at Vanderbilt University Commencement after successfully defending his dissertation in February. Mohamed received his Ph.D. in Biomedical Engineering and is currently a Research Scientist at Facebook Reality Labs in Redmond WA.
DIIGI Lab present research at ARVO Annual Meeting
Graduate students Eric Tang and Joe Malone presented their research at the Association for Research in Vision and Ophthalmology (ARVO) Annual Meeting in Vancouver BC. Joe was a recipient of the Knights Templar Eye Foundation Travel Grant. Congrats Eric and Joe!
DIIGI Lab© 2019