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This technology includes a novel Principal Component Analysis (PCA) based approach to correct motion related B0 changes in PRF thermometry. Proton Resonance Frequency (PRF) thermometry is a widely used Magnetic Resonance Imaging (MRI) based technique to monitor changes in tissue temperature in response to thermal therapy. The use of PRF thermometry with thermal therapy procedures is indispensable to ensure delivery of desired thermal dose to the target tissue, and to minimize unintended damage to the normal tissue.

This technology includes the incorporation of a magnetic field gradient waveform (consisting of two or more pulses) between excitation and encoding to eliminate signal from moving fluid for imaging applications. Proton Resonance Frequency (PRF) thermometry is a widely used Magnetic Resonance Imaging (MRI) based technique to monitor changes in tissue temperature in response to thermal therapy. The use of PRF thermometry with thermal therapy procedures is indispensable to ensure delivery of desired thermal dose to the target tissue, and to minimize unintended damage to the normal tissue.

This technology includes the determination of temperature dependent temporal deviations of the real from the intended gradient waveforms and k-space trajectories during MRI image acquisition, and the use of appropriate temperature dependent pre-compensations to avoid or reduce the image distortion caused by these temporal deviations on the gradient waveforms and k-space trajectories, which will improve imaging quality.

This technology includes a method of correcting the motion during T1 mapping using cardiovascular magnetic resonance imaging (MRI). Ischemic heart disease is the leading cause of death in the United States. The lack of blood supply among myocardial tissue, especially for scar regions, changes the T1 relaxation value of heart muscles. The non-invasive quantification of T1 value of myocardium (T1 mapping) is therefore of great importance for the diagnosis and treatment of cardiovascular disease.

This technology includes the use of nanodiamonds to achieve background-free imaging. We present several techniques to reduce or eliminate background florescence by exploiting properties of the fluorescent nanodiamonds. In particular, magnetic field modulation of the fluorescence intensity offers a simple, robust, and easily adaptable method to obtain background free imaging in a variety of imaging modalities, i.e., fluorescence microscopy and wide field fluorescence animal imaging.

This technology includes a fully automated computer aided diagnosis system to quantify myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) pixel maps from the first-pass contrast-enhanced cardiac magnetic resonance (CMR) perfusion images. This system performs automated image registration, motion compensation, segmentation, and modeling to extract quantitative features from different myocardial regions of interest.

This technology includes a combination of protein biomarkers and clinical risk factors to be used as an In Vitro Diagnostic Multivariate Index Assay (IVDMIA) that can improve the identification of individuals at high risk for atherosclerotic cardiovascular disease (ASCVD) and myocardial infarction (MI). Incorporation of novel protein biomarkers of ASCVD risk into risk assessment algorithms may improve their ability to identify individuals at high risk for ASCVD.

This technology includes an approach that dramatically lessens the effects of depth-dependent degradation in fluorescence microscopy images. First, we develop realistic ‘forward models’ of the depth dependent degradation and apply these forward models to shallow imaging planes that are expected to be relatively free of such degradation. In doing so, we create synthetic image planes that resemble the degradation found in deeper imaging planes. Second, we train neural networks to remove the effect of such degradation, using the shallow images as ground truth.

This technology includes an illuminator and reflector that enables flexible standing wave illumination on an inverted microscope stand, and procedures for using such illumination to improve axial resolution in confocal or instant SIM imaging systems. The axial resolution in conventional fluorescence microscopy is typically limited by diffraction to ~700 nm. This method that improves axial resolution ~7-fold over the diffraction limit, and that can be applied to any fluorescence microscope.

This technology includes algorithms and software that improve the speed of iterative deconvolution, a common method for improving spatial resolution and contrast in fluorescence microscopy images. These algorithms also improve the registration of multiview datasets, and apply deep learning to accelerate spatially varying deconvolution.