Method and Apparatus to Improve an MRI Image

The invention is a method for improving image quality in MR imaging methods using the SENSE (SENSitivity Encoding) method, which is known to have degraded image quality due to numerical ill-conditioning (so called g-factor loss). The invention improves the numerical conditioning by means of an adaptive regularization (matrix conditioning), thereby improving image quality for a given scan time. This is accomplished by adaptively adjusting the regularization parameter for each pixel position to achieve a target ghost artifact suppression.

Generalized MRI Artifact Reduction Using Array Processing Method

The invention is a phased array combining method for reducing artifacts in Magnetic Resonance (MR) imaging. The method uses a constrained optimization that optimizes signal-to-noise subject to the constraint of nulling ghost artifacts at known locations. The method is effective in reducing or canceling artifacts that arise in a wide variety of MR applications, including ghost artifacts from echo planar imaging and Gradient Recalled Echo with Echo Train (FGRE-ET) imaging used in cardiac or other rapid imaging applications.

Real Time Interactive Volumetric Magnetic Resonance Imaging

The invention makes possible "live" volume renderings from a Magnetic Resonance Imaging (MRI) scanner. Previously, volume renderings from MRI data could only be generated off-line, some time after the image data was collected. In one embodiment of the invention, the time between data collection and volume rendering update (the latency) is approximately one third of a second at a frame rate of approximately 10 updates per second. User interaction with the rendering, such as rotation and cut planes, is allowed during imaging.

Neuronal Decoding Algorithm for Prosthetic Limbs

The invention is a new algorithm for decoding neuronal responses based on the discovery that neuronal spike trains can be described using order statistics. The device has applications in the direct control of prosthetic limbs by neuronal signals originating from electrodes placed in the brain. The method allows for decoding neuronal responses by monitoring sequences of potentials from neurons while specific motor tasks are carried out.

Adaptive Sensitivity Encoding Incorporating Temporal Filtering (TSENSE)

The invention is an accelerated magnetic resonance imaging method developed to reduce the total imaging time for gated, segmented cine imaging or to increase the frame rate when imaging dynamic activity, such as heart motion or brain activity. The invention combines temporal filtering (e.g., the UNFOLD method) with a known spatial sensitivity encoding technique (SENSE or SMASH) to achieve a new technique that is the subject of the invention (TSENSE) having a higher degree of alias artifact rejection than could be obtained using either temporal or spatial filtering individually.

Multi-Photon Microscopy System Configured for Multiview Non-Linear Optical Imaging

This invention is a microscopy device and system for multi-photon microscopy utilizing multi-view nonlinear optical imaging. Nonlinear optical imaging remains the premier technique for deep-tissue imaging in which typically a multi photon arrangement may be used to illuminate and excite a sample. However, the penetration depth, signal-to-noise ratio, and resolution of this technique is ultimately limited by scattering. The present system addresses these issues by sequential excitation of a sample through three or more objective lenses oriented at different axes intersecting the sample.

Software for Fully Automating Myocardial Perfusion Quantification

Software is has been developed and available for licensing that fully automates image processing for the quantification of myocardial blood flow (MBF) pixel maps from firstpass contrast-enhanced cardiac magnetic resonance (CMR) perfusion images. The system removes the need for laborious manual quantitative CMR perfusion pixel map processing and can process prospective and retrospective studies acquired from various imaging protocols. In full automation, arterial input function (AIF) images are processed for motion correction and myocardial perfusion images are corrected for intensity bias.

Real Time Medical Image Processing Using Cloud Computing

The invention pertains to a system for reconstructing images acquired from MR and CT scanners in a robust Gadgetron based cloud computing system. A hardware interface connects clinical imaging instruments (e.g., MR or CT scanners) with a cloud computing environment that includes image data reconstruction and processing software not limited by the computational constraints typical of static hardware with finite processor power.

User-friendly, Powerful Software for Analyzing ChIP-Seq Data

The present invention provides a user-friendly software, called PAPST (Peak Assignment and Profile Search Tool for ChIP-Seq), for bench scientists to work with ChIP-Seq data in seconds, allowing the scientists to screen genes against multiple genomic features with ease and efficiency previously not realized. Furthermore, PAPST may be used to identify genes of special significance in a wide variety of biological and biomedical fields, which could lead the discovery of disease-associated genes and the development of therapeutic methods for human diseases.

Software to Improve the Quality of Microscopy Images

Available for licensing and commercial use is software based on an iterative deconvolution procedure that recovers images that have been blurred by a known point spread function. The software provides superior results when multiple independent observations of the same specimen are obtained. An example of such observations might be the multiple views of a specimen collected by a selective illumination plane microscope (SPIM).