Abstract: Examples described herein may predict therapy efficacy and/or therapeutic parameters using a comparison of individual patient status data and brain network response maps for the therapy. For example, VNS parameters may be predicted using a comparison of patient EEG data and brain network response maps of VNS therapy at various parameters.
Abstract: Systems and methods for generating thin slice images from thick slice images are disclosed herein. In some examples, a deep learning system may calculate a residual from a thick slice image and add the residual to the thick slice image to generate a thin slice image. In some examples, the deep learning system includes a neural network. In some examples, the neural network may include one or more levels, where one or more of the levels include one or more blocks. In some examples, each level includes a convolution block and a non-linear activation function block. The levels of the neural network may be in a cascaded arrangement in some examples.
Type:
Grant
Filed:
March 12, 2019
Date of Patent:
February 13, 2024
Assignee:
LVIS Corporation
Inventors:
Zhongnan Fang, Akshay S. Chaudhari, Jin Hyung Lee, Brian A. Hargreaves
Abstract: Examples described herein may predict therapy efficacy and/or therapeutic parameters using a comparison of individual patient status data and brain network response maps for the therapy. For example, VNS parameters may be predicted using a comparison of patient EEG data and brain network response maps of VNS therapy at various parameters.
Abstract: Examples described herein may provide for pre-triggering imaging scans (e.g. fMRI scans) using an electronic timer synchronized to a stimulation system.
Type:
Grant
Filed:
December 12, 2017
Date of Patent:
March 9, 2021
Assignee:
LVIS Corporation
Inventors:
Michael Madsen, Zhongnan Fang, Jin Hyung Lee