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A Method For Digital Pathology Using Augmented Reality

UCLA researchers in the Departments of Electrical Engineering and Computer Engineering have developed a novel method for automated image analysis of digital pathology slides.

Use of a Radiation Detector that Combines Virtual Frisch Grid and Cerenkov Readouts

Researchers at the University of California, Davis have developed a radiation detector for high energy photons that employs a transparent semiconductor with a high index of refraction to combine benefits of Virtual Frisch Grid devices and the readout of Cerenkov light.


Hyperspectral imaging is a technique combining imaging and spectroscopy resulting in images with extraordinary precision and detail. Current approaches to capture hyperspectral images are costly and time-consuming. The proposed technique makes use of inexpensive filters and reduces the number of required exposures, thereby improving the efficiency and practicability of obtaining hyperspectral images.

Breathing Motion Artifact Reduction In CT

UCLA researchers have developed a novel scanning and analysis method for breathing motion-correlated CT that can provide breathing motion-artifacts free images for subsequent use in biomechanical modeling for COPD diagnosis and radiation therapy treatment planning.

New Method for the Detection of Vulnerable Plaques in Coronary Artery Atherosclerotic Disease (CAD)

Heart disease is a major leading cause of morbidity and mortality in the U.S. largely due to coronary artery atherosclerotic disease (CAD), which affects millions and costs billions annually. The concept of plaque vulnerability, based on likelihood of fibroatheroma rupture, has prompted many pursuits to identify high risk lesions, costing $150 million per year. However, identifying vulnerable plaques based on structure, via coronary angiograms or CT/MRI scans, has not translated to improved clinical outcome. Thus, the failure to identify and predict plaques at high risk of rupture, which may lead to myocardial infarction, heart failure and/or sudden cardiac death, is likely because structure may not optimally discern plaque vulnerability. Molecular imaging, in contrast, offers an innovative approach for discriminating the vulnerable plaque in that it not only visualizes structure, but also interrogates underlying molecular function. Based on the current methods to detect plaques, there is a need for a better method for measuring plaque rupture vulnerability.

Intravascular Ultrasound-guided Electrochemical Impedance Spectroscopy (IVUS-EIS) to Assess Lipid-Laden Plaques

UCLA researchers in the Department of Medicine have developed a novel intravascular ultrasound-guided electrochemical impedance spectroscopy (IVUS-EIS) system for the detection of oxLDL-laden plaques in arteries.

Virtual Reality Visualization Of Dynamic Images Using Deformable Image Segmentation

Researchers led by Tzung Hsiai from the David Geffen School of Medicine at UCLA have developed a way to visualize moving objects using virtual reality.

Stereo Image Acquisition By Lens Translation

UCLA researchers in the Department of Mechanical and Aerospace Engineering have developed a novel single-objective lens stereo imaging setup for endoscopic applications.

A New Human-Monitor Interface For Interpreting Clinical Images

UCLA researchers in the Department of Radiological Sciences have invented a novel interactive tool that can rapidly focus and zoom on a large number of images using eye tracking technology.

Incorporation of Mathematical Constraints in Methods for Dose Reduction and Image Enhancement in Tomography

UCLA researchers have developed an algorithm that enables construction of 3D images from tomographic data through iterative methods with the incorporation of mathematical constraints. This methodology is an improvement over conventional techniques as it allows for radiation dose reduction and improved resolution.

Real-Time Tomosynthesis For Radiation Therapy Guidance

UCLA researchers in the Department of Radiological Sciences and Department of Radiation Oncology have developed a real-time tomosynthesis design that can produce sufficient contrast to guide radiation therapy of small lung tumors.

A Method For Accurate Parametric Mapping Based On Characterization Of A Reference Tissue Or Region

UCLA researchers in the Department of Radiology have developed a novel method that addresses a common issue of MRI imaging misinterpretation due to the high field effects of B1+ inhomogeneity.

Dicom/Pacs Compression Techniques

Researchers led by Xiao Hu from the Department of Surgery at UCLA have created a novel and convenient way to compress and query medical images from a PACS system.

Deep-Learning-Based Computerized Prostate Cancer Classification Using A Hierarchical Classification Framework

UCLA researchers in the Department of Radiological Sciences have developed a deep-learning-based computerized algorithm for classification of prostate cancer using multi-parametric-MRI images.

Equally Sloped (Pseudopolar) Tomography With Applications To Biological And Medical Imaging

UCLA researchers in the Department of Physics and Astronomy and the California NanoSystems Institute have developed a new tomographic imagine technique providing higher spatial resolution at a lower radiation dose.

Glucose-conjugated magnetonanoparticles for visualization and treatment of neoplasms and neurological disorders by MRI

Researchers at the UCLA Semel Institute for Neuroscience and Human Behavior have developed magnetic nanoparticles (MNPs) functionalized with deoxyglucose that can be used as tissue-specific contrast agents for MRI. These novel MNPs can help physicians and researchers to differentiate neoplastic, epileptic, parkinsonian, or Alzheimer tissues from normal tissue based on the metabolic activity of the tissue.

Preparation Of Functionalized Polypeptides, Peptides, And Proteins By Alkylation Of Thioether Groups

UCLA researchers in the Departments of Chemistry, Physics, and Bioengineering, led by Dr. Tim Deming of the Bioengineering Department, have developed new methods for adding different functional groups on polypeptides.  The UCLA researchers have used this method to create a platform to create and modify nanoscale vesicles and hydrogels for use in nanoscale drug delivery particles, injectable drug depots, imaging and detection, industrial biomaterials, and wound management.

Fast Implementation Of Equally-Sloped Tomography

Dr. Miao and colleagues at UCLA have developed a novel algorithm that quickly processes high quality image reconstruction of data acquired through Equally-Sloped Tomography.

Improved Shortwave Infrared Polymethine Dyes

UCLA researchers in the Department of Chemistry and Biochemistry have developed improved bright and non-toxic polymethine dyes that will expand current medical optical imaging capabilities.

Collimator/Image Reconstruction Molecular Breast Imaging

MBI and BSGI utilize γ-cameras in a mammographic configuration to provide functional images of the breast. Several studies have confirmed that MBI has a high sensitivity for the detection of small breast lesions, independent of tumor type. A large clinical trial compared MBI with screening mammography in over 1000 women with mammographically dense breast tissue and increased risk of breast cancer and showed that MBI detected two to three times more cancers than mammography. Despite these favorable results, BSGI and MBI have not been widely accepted for breast cancer screening due to greater effective radiation dose compared with mammography. Another disadvantage of MBI is long imaging time, causing discomfort to the patient. Furthermore, while digital breast tomosynthesis (DBT) produces 3D images, resulting in improved cancer detection over mammography, current clinical MBI and BSGI systems produce only 2D images. These disadvantages are due to the use of parallel hole collimator (PHC) with MBI and BSGI, which is inefficient, allowing only gamma rays traveling perpendicular to the detector to be recorded. Furthermore, PHA cannot produce a 3D image with a stationary detector and results in a loss of image resolution with increasing distance between the tumor and the gamma detector.

3D Population Maps for Noninvasively Identifying Phenotypes and Pathologies in Individual Patients

UCLA researchers in the Department of Radiological Sciences have developed a novel computation system that uses large imaging datasets to aid in clinical diagnosis and prognosis.

Systems and Methods for Real-Time Remote 3D Radiotherapy Treatment Monitoring

Researchers from the Department of Radiation Oncology at UCLA have developed a novel method that enables 3D patient monitoring during radiation therapy that enables remote patient visualization with high spatial resolution.

Systems and Methods for Real-Time Radiation Therapy Gantry Collision Detection

Researchers in the UCLA Department of Radiation Oncology have developed a novel means to remotely visualize a radiotherapy treatment room in real-time via 3D camera technology.

Motion-Stabilized Flow Imaging Device

UC Irvine researchers developed a portable, handheld device for dynamically measuring and visualizing blood flow.

Ultrashort Echo Time Magnetization Transfer (UTE-MT) Imaging as a Tool to Aid in the Diagnosis of Osteoporosis

Routine clinical evaluation of osteoporosis (OP) has been focused on dual energy X-ray absorptiometry(DEXA) and/or computed tomography (CT), which provides qualitative analysis of bone mineral (~45% of bone by volume). The majority of bone which is the organic matrix and water (~55% of bone by volume) plays an important role in bone viscosity and strength. Bone mineral density (BMD) by itself only predicts fractures with an accuracy of 30-50%. The overall fracture risk increases 13-fold from ages 60 to 80, but BMD alone only predicts a doubling of the fracture risk. A recent study of over 7806 patients found that only 44% of all non-vertebral fractures occurred in women with a T-score below -2.5 (WHO definition of OP). This percentage dropped to 21% in men. There is a clear need for more sensitive risk assessment tools which not only use BMD, but other determinants of risk such as bone microstructure, porosity, organic matrix and bone water. The organic matrix and water are undetectable with any of the current non-invasive imaging and/or quantification techniques. Magnetic resonance imaging (MRI) detects signals from water in tissues, thus potential for detecting the collagen matrix (bound water) and bone porosity (bulk water). However, bone water has very short transverse relaxation time (T2*) and is undetectable using conventional MR sequences on clinical MR systems.

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