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High-speed machine vision is increasing its importance in both scientific and technological applications. Neuro-inspired photonic computing is a promising approach to speed-up machine vision processing with ultralow latency. However, the…
Time-of-flight (ToF) devices have greatly propelled the advancement of various multi-modal perception applications. However, achieving accurate rendering of time-resolved information remains a challenge, particularly in scenes involving…
Optical imaging through scattering media is a long-standing challenge. Although many approaches have been developed to focus light or image objects through scattering media, they are either invasive, restricted to stationary or…
Research and medicine rely on non-invasive optical techniques to image living tissue with high resolution in space and time. But so far a single data acquisition could not provide entirely diffraction-limited tomographic volumes of rapidly…
Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) enables us to probe the microstructural arrangement of cardiomyocytes within the myocardium in vivo and non-invasively, which no other imaging modality allows. This innovative technology…
Optical Coherence Tomography (OCT) has become an indispensable tool for investigating mesoscopic features in soft matter and fluid mechanics. Its ability to provide high-resolution, non-invasive measurements in both spatial and temporal…
We present a method for estimating dense continuous-time optical flow from event data. Traditional dense optical flow methods compute the pixel displacement between two images. Due to missing information, these approaches cannot recover the…
Ultrasonography is a vital component of modern clinical care, with handheld probes routinely used for diagnostic imaging and procedural guidance. However, handheld ultrasound imaging is limited by factors such as the partial-cross-sectional…
Direct time-of-flight (dToF) sensors are promising for next-generation on-device 3D sensing. However, limited by manufacturing capabilities in a compact module, the dToF data has a low spatial resolution (e.g., $\sim 20\times30$ for iPhone…
Losses should be accounted for in a complete description of quantum imaging systems, and yet they are often treated as undesirable and largely neglected. In conventional quantum imaging, images are built up by coincidence detection of…
Fiber-form optics extends the high-resolution tomographic imaging capabilities of Optical Coherence Tomography (OCT) to the inside of the human body, i.e., endoscopic OCT. However, it still faces challenges due to the trade-off between…
Numerical simulation of atmospheric turbulence is one of the biggest bottlenecks in developing computational techniques for solving the inverse problem in long-range imaging. The classical split-step method is based upon numerical wave…
Capturing depth and reflectivity images at low light levels from active illumination of a scene has wide-ranging applications. Conventionally, even with single-photon detectors, hundreds of photon detections are needed at each pixel to…
Quantum imaging with undetected photons spatially transfers amplitude and phase information from one spectral region of physical interest to another spectral region that is easy to detect. The photon energy of the two spectral regions can,…
Recording and identifying faint objects through atmospheric scattering media by an optical system are fundamentally interesting and technologically important. In this work, we introduce a comprehensive model that incorporates contributions…
As light travels through a disordered medium such as biological tissues, it undergoes multiple scattering events. This phenomenon is detrimental to in-depth optical microscopy, as it causes a drastic degradation of contrast, resolution and…
We present a novel single-shot interferometric ToF camera targeted for precise 3D measurements of dynamic objects. The camera concept is based on Synthetic Wavelength Interferometry, a technique that allows retrieval of depth maps of…
Abdominal CT data are limited by high annotation costs and privacy constraints, which hinder the development of robust segmentation and diagnostic models. We present a Prior-Integrated Variation Modeling (PIVM) framework, a diffusion-based…
Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning and monitoring of many neurological…
Objective: Probe-based confocal endomicroscopy is an emerging high-magnification optical imaging technique that provides in vivo and in situ cellular-level imaging for real-time assessment of tissue pathology. Endomicroscopy could…