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

An innovative imaging system combining X-ray-induced acoustic imaging and CT for enhanced osteoporosis diagnosis.

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

Researchers at the University of California, Davis have developed a technology that significantly improves the timing and spatial resolution of PET scans using dual-ended readout detectors.

Researchers at the University of California, Davis have developed a microscopy system combining optical coherence and confocal fluorescence microscopy for accurate Dry Eye Disease diagnosis.

Glioblastoma is a malignant primary brain tumor that is highly invasive and infiltrative. Surgical resection and radiation therapy are not able to remove all tumor cells. Consequently, residual tumor is found in the majority of patients after surgery, causing early recurrence and decreased survival. Magnetic Resonance Imaging (MRI) is routinely used in the diagnosis, treatment planning and monitoring of glioblastoma. The contrast-enhancing region identified with MRI is generally used to guide surgery and to provide a reference for radiotherapy planning. While edema and non-enhancing regions surrounding the tumor arepotential sites of tumor infiltration, usually they are not included in surgical resection as routine MRI cannot differentiate tumorous tissues in those regions. UC Berkeley researchers have developed a novel MRI technique that can identify, non-invasively and in-vivo, areas of altered iron metabolism associated with tumor activities in the edema tissue surrounding glioblastoma. The technique uniquely delineates a hyperintense area within the edema. The method can be used to guide surgery and radiotherapy and to monitor treatment response.

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

Researchers at the University of California, Davis have developed an intravascular catheter system that integrates Fluorescence Lifetime Imaging (FLIm) with Polarization-Sensitive Optical Coherence Tomography (PS-OCT) for advanced plaque assessment in coronary artery disease.

A novel method using Diffusion Tensor Imaging (DTI) combined with Statistical Parametric Mapping (SPM) as an effective diagnostic tool for Traumatic Brain Injury.

A breakthrough imaging technique that provides high-resolution visualization of optically transparent materials at a low cost.

A novel method for predicting the effective lens position (ELP) in cataract surgery through pre-operative measurements of natural lens curvatures.

An innovative technology that uses dual energy CT to measure blood flow in organs, offering a non-invasive, accurate assessment of diseases like INOCA.

Bento is an open-source software toolkit that uses single-molecule information to enable spatial analysis at the subcellular scale. Bento ingests molecular coordinates and segmentation boundaries to perform three analyses: defining subcellular domains, annotating localization patterns, and quantifying gene-gene colocalization. The toolkit is compatible with datasets produced by commercial and academic platforms. Bento is integrated with the open-source single-cell analysis software ecosystem.

Researchers at the University of California, Davis have developed a technology involving statistically reconstructing positronium (or positron) lifetime imaging (PLI) for use with a positron emission tomography (PET) scanner, to produce images having resolutions better than can be obtained with existing time-of-flight (TOF) systems.

Researchers at the University of California, Davis, have developed a novel imaging system that improves the diagnostic accuracy of PET imaging. The system combines machine learning and computed tomography (CT) imaging to reduce noise and enhance resolution. This novel technique can integrate with commercial PET imaging systems, improving diagnostic accuracy and facilitating superior treatment of various diseases.

Researchers at the University of California, Davis have developed a solid-state device that uses Cherenkov Radiation to emit light at a tunable wavelength in the THz to IR range.

Researchers at the University of California, Davis, have developed a headset (e.g., virtual reality headset) in which two imaging modalities, optical coherence tomography (OCT) and scanning laser ophthalmoscopy (SLO), are incorporated with automated eye tracking and optical adjustment capabilities providing a fully automated imaging system in which patients are unaware that images of the retina are being acquired. Imaging takes place while the patient watches a soothing or entertaining video.

Researchers at the University of California, Davis have developed an optical lens module that uses a metalens or a metalens array having a controllable angular field-of-view.

Researchers at the University of California, Davis have developed two designs capable of capturing hyperspectral images that can be processed using compressive sensing techniques. These advanced component technologies for hyper-spectral imagers realizing 100x reduced size, weight, and power while supporting 1000x framerates in support of high performance.

Researchers at the University of California, Davis have developed a novel cell segmentation technology for accurate analysis of non-spherical cells and that offers a comprehensive, high-throughput approach for analyzing the transcriptomic and metabolomic data to study complex biological processes at the single-cell level.

This technology introduces a novel method for dynamically tuning the optical properties of living cells by expressing cephalopod proteins.

An innovative microscope integrating HSI, FLIM, and SHG for advanced optical metabolic imaging.

A revolutionary laser-based micro-biopsy tool designed for minimally invasive, precise tissue sampling and real-time histological analysis.