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

Browse Category: Imaging > Software

Categories

[Search within category]

Convex Optimized Diffusion Encoding (CODE) For Motion Compensated Diffusion Weighted Magnetic Resonance Imaging With Shortened Echo Times

UCLA researchers in the Department of Radiological Sciences have developed a novel method for diffusion weighted MRI that minimizes echo times and/or incorporates bulk motion compensation through application of a convex optimized diffusion encoding (CODE).

Anisotropic Elastoplasticity For Codimensional Frictional Contact

UCLA researchers in the Department of Mathematics and Department of Computer Science have developed a novel hybrid Lagrangian/Eulerian approach to simulate frictional contact in thin codimensional elastic objects, such as cloth, hair, and knit. It allows a more smooth and vivid animation of those objects with faster speed and higher robustness.

Reducing Computational Complexity of Training Algorithms for Artificial Neural Networks

Researchers at UCLA have developed a novel mathematical theorem to revolutionize the training of large-scale artificial neural networks (ANN).

Geometrical Characterization of Surfaces from Noisy 3D Fluorescence Microscopy Data

A fully automated algorithm to determine the location and curvatures of an object’s surface from 3D fluorescence images.

Deep Learning Microscopy

UCLA researchers in the Department of Electrical Engineering have developed a novel microscopy analysis that improves resolution, field-of-view and depth-of-field in optical microscopy images.

Computational Out-Of-Focus Imaging Increases The Space-Bandwidth Product In Lens-Based Coherent Microscopy

UCLA researchers in the Department of Electrical Engineering have developed a wide-field and high-resolution coherent imaging method that uses a stack of out-of-focus images to provide much better utilization of the space-bandwidth product (SBP) of an objective-lens.

Sparsity-Based Multi-Height Phase Recovery In Holographic Microscopy

UCLA researchers in the Department of Electrical Engineering have developed a sparsity-based phase reconstruction technique implemented in wavelet domain to achieve more than 3-fold reduction in the number of holographic measurements for coherent imaging of densely connected samples with minimal impact on the reconstructed image quality.

A General Noise Suppression Scheme With A Reference Beam In Optical Heterodyne Spectroscopy

A methodology to suppress additive and convolved noise in optical heterodyne signals

Automated Reconstruction Of The Cardiac Chambers From MRI

This is a fast, fully automated method to accurately model a patient’s left heart ventricle via machine learning algorithms.

Developing Physics-Based High-Resolution Head And Neck Biomechanical Models

UCLA researchers in the Department of Radiation Oncology at the David Geffen School of Medicine have developed a new computational method to model head and neck movements during medical imaging/treatment procedures.

Assessment Of Wound Status And Tissue Viability Via Analysis Of Spatially Resolved Thz Reflectometry Maps

UCLA researchers in the Department of Bioengineering have developed an algorithm to assess the burn wound severity and predict its future outcomes using Terahertz imaging.

Quantification Of Plant Chlorophyll Content Using Google Glass

UCLA researchers in the Department of Electrical Engineering have invented a novel device that can quantify chlorophyll concentration in plants using a custom-designed Google Glass app.

Pixel Super-Resolution Using Wavelength Scanning

UCLA researchers have developed a novel way to significantly improve the resolution of an undersampled or pixelated image.

Robust Visual-Inertial Sensor Fusion For Navigation, Localization, Mapping, And 3D Reconstruction

UCLA researchers in the Computer Science Department have invented a novel model for a visual-inertial system (VINS) for navigation, localization, mapping, and 3D reconstruction applications.

Dsp-Sift: Domain-Size Pooling For Image Descriptors For Image Matching And Other Applications

UCLA researchers in the Computer Science Department have invented a novel modification to the scale-invariant feature transform (SIFT) algorithm that shows significant improvement for computer vision applications.

A Method Of Computational Image Analysis For Predicting Tissue Infarction After Acute Ischemic Stroke

UCLA researchers in the Departments of Radiological Sciences and Neurology have designed an algorithm to predict tissue infarctions using pre-therapy magnetic resonance (MR) perfusion-weighted images (pre-PWIs) acquired from patients with acute ischemic stroke. The predictions generated by the algorithm provide information that may assist in physicians’ treatment decisions.

MEMS-Based Mirror Array For Optical Beam Forming And Steering

Self-driving cars, drones, robots and other autonomous systems rely on various sensors for obstacle detection and avoidance to navigate safely through environments. One of the most common methods to sense obstacles is light Detection and Ranging (LiDAR), which uses light in the form of a pulsed (or amplitude/frequency modulated CW) laser to measure variable distances. These light pulses—combined with other data recorded by the airborne system— generate precise, three-dimensional information about the shape of the surrounding environment and its surface characteristics. While LiDAR is a well established and utilized system within many mobility companies, it’s large size and high cost-per-unit has prevented its implementation in many commercial applications. Solid state LiDARs with non-mechanical scanning elements have received increasing interests. In particular, the optical phased array (OPA) provides non-mechanical scanning in a compact form factor. More importantly, at reduced size OPAs enable sophisticated beamforming such as simultaneous scanning, pointing, and tracking of multiple objects, or even direct line-of-sight communications. Unfortunately, at large-scale OPAs have been found to have slow response times, making their application for commercial use impossible. Researchers at the University of California, Berkeley, have designed an optical phased array with rapid response time. This novel technology utilizes arrays of micromirrors actuated by micro-electro-mechanical systems (MEMS). This novel OPA operates with a larger field of view, with a wide range of laser wavelengths, and without the need for high voltage electronics. It is also far more compact and sophisticated than bulky and intrusive mechanical LIDAR technologies.

Software for auto-generation of text reports from radiology studies

Imaging machines used for radiology studies often export data (such as vascular velocities, bone densitometry, radiation dose, etc.) as characters stored in image format. Radiologists are expected to interpret this data and also store it in their text-based reports of the studies. This is usually accomplished by dictating the data into the text report or copying it by typing it. However, these methods are error-prone and time-intensive.

Atom Probe Tomography Method and Algorithm

Most cluster analysis parameters in atom probe tomography (APT) are selected ad hoc. This can often lead to data misinterpretation and misleading results by instrument technicians and researchers. Moreover, arbitrary cluster parameters can have suboptimal consequences on data quality and integrity, leading to inefficiencies for downstream data users. To address these problems, researchers at the University of California, Berkeley, have developed a framework and specific cluster analysis methods to efficiently extract knowledge from better APT data. By using parameter selection protocols with theoretical explanations, this technology allows for a more optimized and robust multivariate statistical analysis technique from the start, thus improving the quality of analysis and outcomes for both upstream and downstream data users.

Software for Differential Dynamic Microscopy (DDMCalc)

A MATLAB code for performing differential dynamic microscopy (DDM).

Sub-Micron Pixelated Filter-Free Color Detector

Conventional cameras achieve color imaging by patterning organic dye color filters on top of photo detectors. However, due to the low absorption coefficients, organic dye filters cannot be made thinner than a few hundred nanometers, forbidding the realization of very small pixels. In addition, they are not durable under ultraviolet illumination or high temperature. Alternatively, optically thick plasmonic color filters have been realized, which can achieve pixel size down to a few microns. They are also superior to organic dyes regarding stability and design flexibility. However, the plasmonics color filters are still based on the conventional filtering scheme, which is intrinsically ineffective. Researchers at the University of California, Berkeley have developed a mechanism to achieve sub-micron pixel detection with very high photon efficiency. This novel mechanism is based on 3D semiconductor particles, which are more sturdy and easier to fabricate comparing to aforementioned techniques. At sub-micron pixel size, these resonant nano-structures outperform conventional color filters, which are limited by detrimental crosstalk between neighboring pixels.

Patient-Specific Ct Scan-Based Finite Element Modeling (FEM) Of Bone

This invention is a software for calculating the maximum force a bone can support. The offered method provides an accurate assessment of how changes in a bone due to special circumstances, such as osteoporosis or a long duration space flight, might increase patient’s risk of fracture.

A Method For Determining Characteristic Planes And Axes Of Bones And Other Body Parts, And Application To Registration Of Data Sets

The invention is a method for deriving an anatomical coordinate system for a body part (especially bone) to aid in its characterization. The method relies on 3-D digital images of an anatomical object, such as CT- or MR-scans, to objectively, precisely, and reliably identify its geometry in a computationally efficient manner. The invention is a great improvement over the current practice of subjective, user-dependent manual data entry and visualization of bones and organs. The applications for well-defined anatomical coordinate systems include robotic surgeries, models for bone density studies, and construction of statistical anatomical data sets.

Camera-Based Reader For Blurry And Low-Resolution 1D Barcodes

Virtually every packaged good is labeled with at least one form of barcode; generally, either by EAN or UPC standards. The success of barcode technology for identification, tracking, and inventory derives from its ability to encode information in a compact fashion with very low associated cost. Barcode reading via dedicated scanners is a mature technology. Commercial laser-based hand-held barcode scanners achieve robust readings. Recently, however, there has been growing interest in accessing barcodes with regular cellphone, rather than with a dedicated devices. Since cellphones are of ubiquitous use, this would enable a multitude of mobile applications. For example, a number of cellphone apps have appeared recently that provide access via barcode reading to the full characteristics and user review for a product found at a store. Unfortunately, cellphone camera images generated by low-grade lenses which produce blurred barcode images. Likewise, motion blur along with low ambient light make barcode reading difficult in certain situations.

  • Go to Page: