A novel non-invasive therapy combining pulsed laser and dual-frequency ultrasound for rapid and precise treatment of port-wine stains.

A lightweight, head-mounted OCT system enabling real-time, high-resolution brain imaging in freely moving small animals.

Quantum‑correlated photon imaging experiments first used pairs of entangled photons so that an image was recovered only from correlations between the two detection paths rather than from either beam alone. Similar correlation and entanglement ideas have been attempted for higher energies and to positron‑annihilation photons, motivating quantum‑based Positron Emission Tomography (PET) concepts in which the additional quantum information carried by annihilation photon pairs could enhance image quality or add new types of contrast beyond conventional PET. In parallel, quantum‑inspired transmission imaging has been proposed as an alternative to Computed Tomography (CT), which today relies on a well‑characterized but fundamentally stochastic X‑ray source, and is limited by Poisson photon statistics, dose requirements, and capped contrast for soft‑tissue. Traditional X‑ray and CT imaging are governed by Poisson statistics, where independent, random photon arrivals make the variance equal to the mean, and has fundamentally bound SNR for a given dose. Research on quantum‑correlated transmission schemes has looked at image formation with higher‑order correlations between photons (rather than simple independent counting) such that performance is no longer capped by standard Poisson statistics, which can in principle lead to superior SNR and sharper anatomical detail at a given dose. To date, quantum‑based X‑ray implementations of this idea have largely relied on spontaneous parametric down‑conversion (SPDC) to generate entangled or correlated photon pairs, but SPDC at X‑ray‑level energies has extremely low conversion efficiency and pair rates—often only a few pairs per second—rendering such medical or biological imaging impractical. Quantum correlation of Annihilation Photon Imaging (QAPI) brings the correlation concepts into a PET‑like regime by using positron annihilation as a bright source of 511 keV gamma‑ray pairs while assuming a transmission‑imaging role similar to CT. QAPI is designed to exploit the strengths of both worlds: unlike CT, it can count the incident annihilation photons via the idler channel and operate in a high‑transmission regime that permits binomial transmission statistics. The PET‑like 511 keV photons introduce challenges that do not exist for CT, including low interaction probability in tissue and detectors, reduced single‑photon detection efficiency, and the need for precise coincidence timing between the signal and idler counts. For any high‑energy, photon-based imaging, including emerging quantum schemes, there is a fundamental tension between dose (especially for biological tissues that are highly susceptible to damage, cell death, or mutation when exposed to ionizing radiation) and the photon statistics needed for adequate SNR. Moreover, the dose‑normalized performance for quantum approaches is still not well established.

Researchers at the University of California, Davis have developed a machine learning system for accurately separating fetal signals from mixed maternal-fetal photoplethysmography signals acquired non-invasively to enable fetal physiological parameter monitoring.

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Researchers at the University of California, Davis have developed a machine learning system that accurately detects and estimates retinal inflammation severity in uveitis patients using non-invasive OCT B-scan images.

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A breakthrough one-wire EEG cap with embedded electrode chips provides ultra-sensitive, noise-immune, wide-band brain signal acquisition. It enables non-invasive, real-time, high-resolution recording using dry electrodes, ideal for wearable and clinical neuro-technology applications.

An innovative non-invasive device that accurately determines the age of bruises for all skin types and tones, designed to assist in forensic investigations and medical diagnostics.

Researchers at the University of California, Davis have developed a solid-state X-ray imager with high temporal resolution.

An advanced AI-driven system for synthetic medical data generation and precise segmentation of cardiac MRI to enhance accuracy and efficiency in cardiovascular health.

Researchers at the University of California, Davis have developed an imaging scheme for two-photon microscopes enhancing speed and resolution in neuroscience research.

Researchers at the University of California, Davis have developed isolated peptides that selectively bind M1 and M2 macrophages to enable precise diagnosis and targeted treatment of macrophage-associated diseases, including cancer.

Researchers at the University of California, Davis have developed a nanoparticle system combining photothermal therapy and chemotherapy for enhanced cancer treatment.

Researchers at the University of California, Davis have developed an advanced multi x-ray source array system employing dual cathode designs that enhance computed tomography (“CT”) imaging by enabling pulsed, spatially multiplexed x-ray emission with reduced artifacts.

A medical device that uses machine learning and augmented reality to project precise surgical guides onto 3D patient anatomy, enabling real-time surgical guidance and remote expert collaboration.

A novel protoacoustic imaging method and apparatus providing affordable, real-time verification of proton range and quantification of radiation dose during proton therapy to improve treatment precision and patient outcomes.

An advanced geometric method for comprehensive 3D cardiac strain analysis, enhancing diagnosis and monitoring of myocardial diseases.

This technology leverages X-ray-induced acoustic phenomena for real-time, in-line verification of photon beam location and dose during cancer radiotherapy.

A novel technology for real-time, non-invasive monitoring and adaptive control of electron radiotherapy treatments using acoustic signals.

X-radiation (X-ray) imaging is one of the most common imaging techniques in medicine. Presently, thin-film transistor flat panel detectors are the gold standard for X-ray detection; however, these detectors average across the absorbed X-ray spectrum and thus suffer from poor material decomposition and lesion differentiation. Modern efforts to address this focus on three methods of energy differentiation: dual-shot, photon counting, and dual-layer detectors. Dual-shot detection utilizes a single detector to image a patient with two shots of X-rays at low and high energies. While this has been shown to effectively differentiate between soft and hard tissues, (e.g., chest radiography) this results in a higher dose level to the patient and motion artifacts from slight movement between images. Photon counting detectors offer an alternative to multiple shots, providing high spatial resolution, low dose, and multiple energy binning with photon weighting. However, these detectors also require more complex circuit design for fast readout, have limited material options with great enough yield and detective quantum efficiency at low to mid energy ranges, and are limited in detective area. Dual-layer detectors that stack two detector layers to each process low and high energy X-rays remove motion artifacts by utilizing a single shot of polyenergetic X-rays. These most commonly employ two indirect detectors separated by a Cu filtering layer, which photon-starves the second higher energy detector. Unfortunately, this also requires a higher X-ray intensity, resulting in a higher dose level to the patient.

In PET imaging, patient motion, such as respiratory and cardiac motion, are a major source of blurring and motion artifacts. Researchers at the University of California, Davis have developed a technology designed to enhance PET imaging resolution without the need for external devices by effectively mitigating these artifacts