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Ryan P. McNabb

Publications and source records attributed to Ryan P. McNabb.

5 recordsLinked to original sources

OCTN: Neural OCT Representations for Robot-Guided Precision Intervention

Optical coherence tomography (OCT) offers compact, contactless, micron-scale imaging suitable for intraoperative guidance, but native OCT volumes are discretely sampled, anisotropic, and currently inefficient for downstream geometric reasoning and robot integration. We present OCTN (pronounced "octane"), an implicit neural representation framework that converts volumetric OCT scans into a continuous, differentiable, and spatially faithful tissue-intensity field. OCTN uses a two-stage hybrid training strategy that combines supervision from acquired voxels with inter-slice interpolations, preserving B-scan fidelity while improving continuity in sparsely sampled regions. For versatility, we first show that OCTN enables fast volumetric reasoning by storing the learned tissue representation natively on the GPU, supporting intensity-based spatial queries with up to 43x speedup over conventional CPU processing. We then demonstrate OCTN-enabled OCT-guided robotic laser surgery where the continuous tissue representation supports implicit surface discovery and surface-constrained path planning via multiple optimization strategies, including Newton- and SGD-based optimization. Next, OCTN enables reconstruction of dense volumetric structure from sparsely acquired B-scans, while reducing acquisition time by 4x and preserving clinically relevant structures. Across the newly generated Duke TissueOCT dataset and public OCT datasets, OCTN achieves robust, high-fidelity reconstruction with PSNR > 30 dB and training time < 10 s, while preserving surface consistency within 10 $μ$m Chamfer distance relative to baseline reconstruction. The TissueOCT dataset and code are publicly available at raprakashvi.github.io/octn

cs.RO

See, Plan, Cut: MPC-Based Autonomous Volumetric Robotic Laser Surgery with OCT Guidance

Robotic laser systems offer the potential for sub-millimeter, non-contact, high-precision tissue resection, yet existing platforms lack volumetric planning and intraoperative feedback. We present RATS (Robot-Assisted Tissue Surgery), an intelligent opto-mechanical, optical coherence tomography (OCT)-guided robotic platform designed for autonomous volumetric soft tissue resection in surgical applications. RATS integrates macro-scale RGB-D imaging, micro-scale OCT, and a fiber-coupled surgical laser, calibrated through a novel multistage alignment pipeline that achieves OCT-to-laser calibration accuracy of 0.161+-0.031mm on tissue phantoms and ex vivo porcine tissue. A super-Gaussian laser-tissue interaction (LTI) model characterizes ablation crater morphology with an average RMSE of 0.231+-0.121mm, outperforming Gaussian baselines. A sampling-based model predictive control (MPC) framework operates directly on OCT voxel data to generate constraint-aware resection trajectories with closed-loop feedback, achieving 0.842mm RMSE and improving intersection-over-union agreement by 64.8% compared to feedforward execution. With OCT, RATS detects subsurface structures and modifies the planner's objective to preserve them, demonstrating clinical feasibility.

cs.RO

Computational 3D microscopy with optical coherence refraction tomography

Optical coherence tomography (OCT) has seen widespread success as an in vivo clinical diagnostic 3D imaging modality, impacting areas including ophthalmology, cardiology, and gastroenterology. Despite its many advantages, such as high sensitivity, speed, and depth penetration, OCT suffers from several shortcomings that ultimately limit its utility as a 3D microscopy tool, such as its pervasive coherent speckle noise and poor lateral resolution required to maintain millimeter-scale imaging depths. Here, we present 3D optical coherence refraction tomography (OCRT), a computational extension of OCT which synthesizes an incoherent contrast mechanism by combining multiple OCT volumes, acquired across two rotation axes, to form a resolution-enhanced, speckle-reduced, refraction-corrected 3D reconstruction. Our label-free computational 3D microscope features a novel optical design incorporating a parabolic mirror to enable the capture of 5D plenoptic datasets, consisting of millimetric 3D fields of view over up to $\pm75^\circ$ without moving the sample. We demonstrate that 3D OCRT reveals 3D features unobserved by conventional OCT in fruit fly, zebrafish, and mouse samples.

physics.optics

High-speed multiview imaging approaching 4pi steradians using conic section mirrors: theoretical and practical considerations

Illuminating or imaging samples from a broad angular range is essential in a wide variety of computational 3D imaging and resolution-enhancement techniques, such as optical projection tomography (OPT), optical diffraction tomography (ODT), synthetic aperture microscopy, Fourier ptychographic microscopy (FPM), structured illumination microscopy (SIM), photogrammetry, and optical coherence refraction tomography (OCRT). The wider the angular coverage, the better the resolution enhancement or 3D resolving capabilities. However, achieving such angular ranges is a practical challenge, especially when approaching plus-or-minus 90 degrees or beyond. Often, researchers resort to expensive, proprietary high numerical aperture (NA) objectives, or to rotating the sample or source-detector pair, which sacrifices temporal resolution or perturbs the sample. Here, we propose several new strategies for multi-angle imaging approaching 4pi steradians using concave parabolic or ellipsoidal mirrors and fast, low rotational inertia scanners, such as galvanometers. We derive theoretically and empirically relations between a variety of system parameters (e.g., NA, wavelength, focal length, telecentricity) and achievable fields of view (FOVs) and importantly show that intrinsic tilt aberrations do not restrict FOV for many multi-view imaging applications, contrary to conventional wisdom. Finally, we present strategies for avoiding spherical aberrations at obliquely illuminated flat boundaries. Our simple designs allow for high-speed multi-angle imaging for microscopic, mesoscopic, and macroscopic applications.

physics.optics

In Vivo Quantitative Analysis of Anterior Chamber White Blood Cell Mixture Composition Using Spectroscopic Optical Coherence Tomography

Anterior uveitis is the most common form of intraocular inflammation, and one of its main signs is the presence of white blood cells (WBCs) in the anterior chamber (AC). Clinically, the true composition of cells can currently only be obtained using AC paracentesis, an invasive procedure to obtain AC fluid requiring needle insertion into the AC. We previously developed a spectroscopic optical coherence tomography (SOCT) analysis method to differentiate between populations of RBCs and subtypes of WBCs, including granulocytes, lymphocytes and monocytes, both in vitro and in ACs of excised porcine eyes. We have shown that different types of WBCs have distinct characteristic size distributions, extracted from the backscattered reflectance spectrum of individual cells using Mie theory. Here, we further develop our method to estimate the composition of blood cell mixtures, both in vitro and in vivo. To do so, we estimate the size distribution of unknown cell mixtures by fitting the distribution observed using SOCT with a weighted combination of reference size distributions of each WBC type calculated using kernel density estimation. We validate the accuracy of our estimation in an in vitro study, by comparing our results for a given WBC sample mixture with the cellular concentrations measured by a hemocytometer and SOCT images before mixing. We also conducted a small in vivo quantitative cell mixture validation pilot study which demonstrates congruence between our method and AC paracentesis in two patients with uveitis. The SOCT based method appears promising to provide quantitative diagnostic information of cellular responses in the ACs of patients with uveitis.

physics.med-ph