Learn more about UC TechAlerts – Subscribe to categories and get notified of new UC technologies

Browse Category: Medical > Imaging

Categories

[Search within category]

Modular Piezoelectric Sensor Array with Beamforming Channels for Ultrasound Imaging

Researchers at the University of California, Davis have developed a large area sensor array for ultrasound imaging systems that utilizes high-bandwidth piezoelectric sensors and modular design elements.

Templated Synthesis Of Metal Nanorods

Brief description not available

Biosensor - Comprised of “Turn-on” Probes - with the Ability to Detect DNA Sequences in Living Cells

Researchers have developed a split-enzyme system that can detect genetic information in living cells by using luciferase linked to programmable DNA-binding domains.

Magnetically Responsive Photonic Nanochains

Brief description not available

(SD2020-421) Virtual Electrodes for Imaging of Cortex-Wide Brain Activity: Decoding of cortex-wide brain activity from local recordings of neural potentials

As an important tool for electrophysiological recordings, neural electrodes implanted on the brain surface have been instrumental in basic neuroscience research to study large-scale neural dynamics in various cognitive processes, such as sensorimotor processing as well as learning and memory. In clinical settings, neural recordings have been adopted as a standard tool to monitor the brain activity in epilepsy patients before surgery for detection and localization of epileptogenic zones initiating seizures and functional cortical mapping. Neural activity recorded from the brain surface exhibits rich information content about the collective neural activities reflecting the cognitive states and brain functions. For the interpretation of surface potentials in terms of their neural correlates, most research has focused on local neural activities.   From basic neuroscience research to clinical treatments and neural engineering, electrocorticography (ECoG) has been widely used to record surface potentials to evaluate brain function and develop neuroprosthetic devices. However, the requirement of invasive surgeries for implanting ECoG arrays significantly limits the coverage of different cortical regions, preventing simultaneous recordings from spatially distributed cortical networks. However, this rich information content of surface potentials encoded for the large-scale cortical activity remains unexploited and little is known on how local surface potentials are correlated with the spontaneous neural activities of distributed large-scale cortical networks. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

(SD2019-220) Spatiotemporal resolution enhancement of biomedical images

Cardiac MRI is the clinical reference standard for visual and quantitative assessment of heart function. Specifically, cine balanced steady-state free precession (SSFP) can yield cardiac images with high myocardium–blood pool contrast for evaluation of left ventricular (LV) function. However, MRI suffers from long acquisition times, often requiring averaging across multiple heartbeats, and necessitates a trade-off among spatial resolution, temporal resolution, and scan time. Clinically, radiologists are forced to balance acquisition time with resolution to fit clinical needs, and certain applications such as real-time imaging may require small acquisition matrices. Image scaling is typically performed by using conventional upscaling methods, such as Fourier domain zero padding and bicubic interpolation. These methods, however, do not readily recover spatial detail, such as the myocardium–blood pool interface or delineation of papillary muscles.

Fetal Oximetry Measurement via Maternal Transabdominal Spectroscopy

Researchers at the University of California, Davis have developed a non-invasive, near-infrared, spectroscopy technique that measures fetal oxygen saturation via the maternal abdomen.

High-Frequency Imaging and Data Transmission Using a Re-configurable Array Source with Directive Beam Steering

Researchers at the University of California, Davis have developed a reconfigurable radiator array that produces a high frequency directed beam via uninterrupted, scalable, electronic beam steering.

Motor Drive Unit for Combined Optical Coherence Tomography and Fluorescence Lifetime Imaging of Intraluminal Structures

Researchers at the University of California, Davis have designed a motor drive unit that enables combined fluorescence lifetime imaging and optical coherence tomography of luminal structures.

2-D Polymer-Based Device for Serial X-Ray Crystallography

Researchers at the University of California, Davis have developed a single-use chip for the identification of protein crystals using X-ray based instruments.

(SD2021-402) Fully Automated Deep Learning‐Based Background Phase Error Correction for Abdominopelvic 4D Flow MRI

4D Flow MRI has become increasingly valuable for the qualitative and quantitative assessment of cardiovascular disease. Since all measurements can be obtained following image acquisition without the need for targeted ultrasonographic windows or placement of 2D phase contrast planes at the time of the exam, 4D Flow provides versatility that can be essential in the diagnostic process.However, the correction of magnetic eddy current-related background phase error remains a critical bottleneck in abdominal applications.

(SD2021-221) Automated deep correction of MRI phase‐error

Time-resolved 3D phase-contrast MRI with three-dimensional velocity encoding (4D Flow MRI) has become increasingly valuable for the evaluation of cardiovascular disease. While cardiothoracic and neurovascular applications have grown rapidly, a limiting factor for abdominal applications is the correction of magnetic eddy current-related background phase error, which can be more challenging to reliably correct in abdominopelvic regions due to complex vascular and soft tissue geometry. Phase-error correction is essential for both quantification of blood flow as well as for visualization.

(SD2021-401) Automated Correction of Background Phase Error for Cerebrovascular 4D Flow MRI

Currently, there are no automated solutions for phase‐error correction that are effective for brain imaging.

Improving Perfusion Magnetic Resonance Imaging Using Ultra-Fast Arterial Spin Labeling

Prof. Jia Guo and colleagues from the University of California, Riverside have developed a method for improving perfusion Magnetic Resonance Imaging (MRI) using Velocity Selective Arterial Spin Labeling (VSASL). This method uses VS labeling pulses that are capable to only label the blood that is moving within a narrow band of velocities and keep the blood moving at higher velocities unperturbed. This creates a small bolus of label that can be detected readily and quickly. This method provides MRI imaging that is far superior than conventional ASL MRI techniques with a doubled temporal resolution, improved signal-to-noise ratio (SNR) efficiency and quantification accuracy. Fig 1: Schematics showing how UCR’s narrow-band velocity selectivity enables ultra-fast perfusion imaging  

Protein Inhibitor of Type II-A CRISPR-Cas System

The inventors have discovered three protein inhibitors of the type II-A CRISPR-Cas system that specifically inhibit Cas9 from staphylococcus aureus. This finding is of potential importance to many companies in the CRISPR space. 

Advanced Imaging By LASER-Trained Algorithms Used To Process Broad-Field Light Photography and Videography

Diagnosing retinal disease, which affects over 200 million people worldwide, requires expensive and complicated analysis of the structure and function of retinal tissue. Recently, UCI developed a training algorithm which, for the first time, is able to assess tissue health from images collected using more common and less expensive optics.

Method for Motion Sensing in MRI Using Preamplifier RF Intermodulation

The inventors have developed a new flexible motion sensing method that exploits nonlinear intermodulation of MRI receiver coil preamplifiers to sense the motion of a subject in an MRI scanner without on-subject hardware. The method transmits two tones at two different frequencies, f1 and f2, designed to be received at frequency f_BPT by the receiver via intermodulation, where f1 and f2 are much greater than the MRI center frequency. These signals are picked up by the receiver coils, mixed at the pre-amplification stage by intermodulation, then digitized by the receiver chain. The method is 20 times more sensitive to motion than the state-of-the-art Pilot Tone (PT) method of motion sensing. The inventors have demonstrated the method with second order intermodulation. Additionally, more transmitters can be used, each with a different set of frequencies. Higher frequency tones enable greater sensitivity to subject motion. This method enables the detection of motion at multiple temporal and spatial scales, for example, breathing and rigid motion of the head. The method is used simultaneously with conventional MR imaging and does not adversely impact the signal-to-noise ratio (SNR) of the acquired MR image. The method has been demonstrated using inexpensive consumer grade hardware for the 2.4GHz ISM band as a proof-of-concept. Since the MR signal is small (< -30dBm), little transmit power is necessary to induce an intermodulation signal similar in amplitude to the MR signal.

Protein Inhibitor of Type VI-B CRISPR-Cas System

The inventors have discovered the first protein inhibitor of the type VI-B CRISPR-Cas system. By controlling this CRISPR system, one could possibly ameliorate the toxicity and off-target cleavage activity observed with the use of the type VI CRISPR system. Moreover, these proteins can also serve as an antidote for instances where the use of CRISPR-Cas technology poses a safety risk. Additionally, this technology can also be used for engineering genetic circuits in mammalian cells. This finding is of potential importance to many companies in the CRISPR space. 

Facile, Excitation-Based Spectral Microscopy For Fast Multicolor Imaging And Quantitative Biosensing

The number of color channels that can be concurrently probed in fluorescence microscopy is severely limited by the broad fluorescence spectral width. Spectral imaging offers potential solutions, yet typical approaches to disperse the local emission spectra notably impede the attainable throughput.    UC Berkeley researchers have discovered methods and systems for simultaneously imaging up to 6 subcellular targets, labeled by common fluorophores of substantial spectral overlap, in live cells at low (~1%) crosstalks and high temporal resolutions (down to ~10 ms), using a single, fixed fluorescence emission detection band. 

Single Catheter System Combining Intravascular Ultrasound and Fiber-Based Fluorescence Lifetime Imaging

Researchers at the University of California, Davis have developed a catheter device that combines intravascular ultrasound with fluorescence lifetime imaging to better detect significant vascular conditions.

Deep Learning Techniques For In Vivo Elasticity Imaging

Imaging the material property distribution of solids has a broad range of applications in materials science, biomechanical engineering, and clinical diagnosis. For example, as various diseases progress, the elasticity of human cells, tissues, and organs can change significantly. If these changes in elasticity can be measured accurately over time, early detection and diagnosis of different disease states can be achieved. Elasticity imaging is an emerging method to qualitatively image the elasticity distribution of an inhomogeneous body. A long-standing goal of this imaging is to provide alternative methods of clinical palpation (e.g. manual breast examination) for reliable tumor diagnosis. The displacement distribution of a body under externally applied forces (or displacements) can be acquired by a variety of imaging techniques such as ultrasound, magnetic resonance, and digital image correlation. A strain distribution, determined by the gradient of a displacement distribution, can be computed (or approximated) from measured displacements. If the strain and stress distributions of a body are both known, the elasticity distribution can be computed using the constitutive elasticity equations. However, there is currently no technique that can measure the stress distribution of a body in vivo. Therefore, in elastography, the stress distribution of a body is commonly assumed to be uniform and a measured strain distribution can be interpreted as a relative elasticity distribution. This approach has the advantage of being easy to implement. The uniform stress assumption in this approach, however, is inaccurate for an inhomogeneous body. The stress field of a body can be distorted significantly near a hole, inclusion, or wherever the elasticity varies. Though strain-based elastography has been deployed on many commercial ultrasound diagnostic-imaging devices, the elasticity distribution predicted based on this method is prone to inaccuracies.To address these inaccuracies, researchers at UC Berkeley have developed a de novo imaging method to learn the elasticity of solids from measured strains. Our approach involves using deep neural networks supervised by the theory of elasticity and does not require labeled data for the training process. Results show that the Berkeley method can learn the hidden elasticity of solids accurately and is robust when it comes to noisy and missing measurements.

Novel Positron Emission Tomography Agents for Imaging Neurodegeneration

New positron emission tomography (PET) imaging agent developed that uniquely binds to synucleinopathies and tauopathies in the Parkinson’s brain and may therefore serve as an early diagnostic marker.

Improved guide RNA and Protein Design for CasX-based Gene Editing Platform

The inventors have developed two new CasX gene-editing platforms (DpbCasXv2 and PlmCasXv2) through rationale structural engineering of the CasX protein and gRNA, which yield improved in vitro and in vivo behaviors. These platforms dramatically increase DNA cleavage activity and can be used as the basis for further improving CasX tools.The RNA-guided CRISPR-associated (Cas) protein CasX has been reported as a fundamentally distinct, RNA-guided platform compared to Cas9 and Cpf1. Structural studies revealed structural differences within the nucleotide-binding loops of CasX, with a compact protein size less than 1,000 amino acids, and guide RNA (gRNA) scaffold stem. These structural differences affect the active ternary complex assembly, leading to different in vivo and in vitro behaviors of these two enzymes.

Elastography based on X-Ray Ct and Sound Wave Integration

Researchers at UCI have created an elastography technique, which combines X-ray computed tomography (CT) and sound wave integration.  This adapted elastographic technique avoids the issues faced by ultrasound alone and permits medical imaging of deep tissue and measures the mechanical properties of materials.

  • Go to Page: