University of Illinois

Osf Healthcare System

Osf Healthcare

Bradley P Sutton

Curtis L Johnson

Matthew Bramlet

Joseph L Holtrop

John G Georgiadis

Luisa Ciobanu

Kevin Urbain

Xi Peng

Diego Hernando

Anh Tu Van

Andres Maldonado

James Evans

Michael Xu

Gabrielle Fournet

Nathan Soria

Jing-Rebecca Li

Alexander M Cerjanic

Denis LeBihan

Bryce L Ching

Yogatheesan Varatharajah

Aspects of the subject disclosure may include, for example, co-registering MRI data with CT data to derive merged data, the MRI data and the CT data being associated with an anatomical part of a patient, the MRI data being obtained prior to implantation of a plurality of electrodes into the anatomical part and the CT data being obtained after the implantation of the plurality of electrodes, performing segmentation on the merged data to identify locations of the plurality of electrodes, resulting in identified locations, localizing a region of interest in the merged data based on the identified locations of the plurality of electrodes and based on activity recordings relating to the anatomical part, and generating a model of the anatomical part by performing multimodal image fusion of the activity recordings and the merged data to derive an output for VR viewing or manipulation. Additional embodiments are disclosed.

Automatic segmentation and multimodal image fusion for stereoelectroencephalographic (SEEG) analysis in virtual reality (SAVR)

Aspects of the subject disclosure may include, for example, a method comprising: receiving, by a processing system including a processor, an input three-dimensional dataset comprising a first plurality of two-dimensional images of all or a portion of a subject; applying, by the processing system, bias field correction to the input three-dimensional dataset to generate a corrected three-dimensional dataset comprising a second plurality of two-dimensional images; and generating, by the processing system, a labeled three-dimensional dataset comprising a third plurality of two-dimensional images, wherein the labeled three-dimensional dataset further comprises one or more labels indicating an anatomical structure, and wherein the labeled three-dimensional dataset is generated via a convolutional neural network based upon the corrected three-dimensional dataset and based upon a previously trained three-dimensional dataset. Additional embodiments are disclosed.

Apparatus and method for producing three-dimensional models from magnetic resonance imaging

Aspects of the subject disclosure may include, for example, obtaining first magnetic resonance imaging (MRI) data of a subject, wherein the first MRI data is obtained during a first scan of a subject, wherein the first scan has a first diffusion sampling time, and wherein the first diffusion sampling time is selected in order to facilitate use of the first MRI data to determine a first Intravoxel Incoherent Motion (IVIM) effective diffusion coefficient in a Stationary Random Flow (SRF) regime; obtaining second MRI data of the subject, wherein the second MRI data is obtained during a second scan of the subject, wherein the second scan has a second diffusion sampling time, wherein the second diffusion sampling time is longer than the first diffusion sampling time, and wherein the second diffusion sampling time is selected in order to facilitate use of the second MRI data to determine a second IVIM effective diffusion coefficient in a pseudodiffusion regime; determining a blood velocity value based upon the first MRI data; and determining a segment length value based upon the second MRI data. Additional embodiments are disclosed.

Measuring blood vessel characteristics with MRI

A method and system provides an acquisition scheme for generating magnetic resonance elastography displacement data with whole-sample coverage, high spatial resolution, and adequate SNR in a short scan time. The method and system can acquire in-plane and through-plane k-space shots over a volume of a sample divided into a plurality of slabs that each include a plurality of non-adjacent slices to obtain three dimensional multiband, multishot data, can apply multiband radio frequency refocusing pulses to the sample, can acquire navigators before readout, and can correct for non-linear motion errors.

Multiband, multishot magnetic resonance elastography

Magnetic resonance elastography (MRE) is an imaging technique for estimating the stiffness of tissues non-invasively. Shear waves are generated via external mechanical actuation and the tissue imaged with a specially designed MR pulse sequence. The resulting images are used to calculate the underlying properties. The application provides methods for acquiring MRE data using a single shot, echo planar imaging readout. The purpose of the developed sequence is to acquire MRE data using a single-shot, echo-planar imaging readout, avoiding to need for off-line image processing.

Echo-planar imaging magnetic resonance elastography pulse sequence

A method and system provides an acquisition scheme for generating MRE displacement data with whole-sample coverage, high spatial resolution, and adequate SNR in a short scan time. The method and system can acquire in-plane k-space shots over a volume of a sample divided into a plurality of slabs that each include a plurality of slices to obtain three dimensional multislab, multishot data, can apply refocusing pulses to the sample, can acquire navigators after the refocusing pulses, and can correct for phase errors based on an averaging of the navigators.

Three dimensional multislab, multi-shot magnetic resonance elastography

Aspects of the subject disclosure include a system that applies magnetic resonance elastography to a sample to obtain uncorrected k-space data where the magnetic resonance elastography utilizes a multi-shot spin-echo sequence with variable density spiral readout gradients, and adjusts the uncorrected k-space data to corrected k-space data by adjusting a k-space trajectory by shifting a center point for each shot to a new center point according to signal intensity and by adjusting a phase for each shot based on a phase offset that is determined according to the signal intensity.

Method and system for multi-shot spiral magnetic resonance elastography pulse sequence

A method for correcting motion-induced phase errors in diffusion-weighted k-space data acquired with a magnetic resonance imaging (MRI) system is provided. The MRI system is directed to acquire the following data from an imaging volume: three-dimensional diffusion-weighted k-space data, three-dimensional diffusion-weighted navigator data, three-dimensional non-diffusion-weighted k-space data, and three-dimensional non-diffusion-weighted navigator data. Initial estimates of k-space shift values and a constant phase offset value are calculated using the three-dimensional diffusion-weighted navigator data and the three-dimensional non-diffusion-weighted navigator data. These initial k-space shift values and constant phase offset value are then updated by iteratively minimizing a cost function that relates the phase of the diffusion-weighted k-space data to the phase of the non-diffusion-weighted k-space data, as shifted by the initial k-space shift values and constant phase offset value. The diffusion-weighted k-space data is then corrected for motion-induced phase errors using the updated k-space shift values and constant phase offset value.

Method for correcting motion-induced phase errors in magnetic resonance imaging

A method for imaging neuromuscular coupling and sensory processing with magnetic resonance imaging ('MRI') is provided. More specifically, a method for examining the control that a subject's brain has over muscular motion, including both prompted and incidental actions, is provided. A dynamic acquisition is performed to rapidly acquire anatomical images of a desired muscle. This dynamic acquisition is interleaved with a functional acquisition that targets the cortical areas that are responsible for controlling, or processing, signals from the desired muscular region. By interleaving these two acquisitions, synchronized image information about the motion of the muscle along with the neuronal activity associated with the control of the muscle is acquired. Interleaving these data acquisitions also allows imaging of brain and muscle at substantially the same time, thereby reducing errors and pinpointing activity.

Method for acquiring dynamic motion images to guide functional magnetic resonance imaging analysis of motor tasks

A method for imaging a brain of a subject includes providing a cognitive task for the subject or measuring resting state blood flow without a cognitive task, applying a saturation pulse sequence to saturate a slice within an imaging volume in the subject, and applying an imaging pulse sequence to acquire data from the imaging volume. A saturated image is acquired shortly after termination of the saturation pulse sequence and a non-saturation image is acquired after spins flowing through the saturated slice have recovered. The saturation image and the non-saturation image are subtracted to generate a blood velocity or perfusion enhanced difference image indicating portions of the brain active during the cognitive task. When measuring resting state blood flow without a cognitive task, the method includes acquiring a calibration scan and performing a quantitative evaluation of the blood velocity perpendicular to the saturated slice.

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Savoy, IL, United States of America

Bradley P Sutton