Cortechs Labs, Inc.

University of California

Zepmed, LLC

Nathan S White

Sebastian Magda

Christopher N Airriess

Anders M Dale

Douglas Bates

The disclosed technology relates generally to medical imaging, and more particularly, some embodiments relate to systems and methods for creating and using a covariate modulated or 'dynamic' atlas. Some embodiments of the disclosure provide a method for predicting an alas using General Additive Model (GAM) parameters, wherein the GAM parameters are derived by registering (and optionally segmenting) a plurality of image data sets from a plurality of different subjects to an initial atlas estimate (e.g., a seed atlas), and analyzing the resulting registration, segmentation, and intensity parameters as correlated with input covariates.

Covariate modulate atlas

The disclosure herein provides methods, systems, and devices for automated reorientation and/or analysis of medical scans and/or images. The methods, systems, and devices for automated analysis of medical scans can be configured to mark, score, grade, and/other otherwise classify medical scans that are more time-sensitive, severe, and/or the like to allow a medical professional reviewing and/or analyzing medical scans to view and/or analyze such scans more efficiently by using a common image orientation and/or taking into account knowledge of the risk of severity, time-sensitiveness, and/or other priority.

Methods, systems, and devices for automated analysis and management of medical scans

Methods, devices and systems are disclosed for measuring biological tissue parameters using restriction spectrum magnetic resonance imaging. In one aspect, a method of characterizing a biological structure includes determining individual diffusion signals from magnetic resonance imaging (MRI) data in a set of MRI images that include diffusion weighting conditions (e.g., diffusion gradient directions, diffusion gradient strengths, sensitivity factors (b-values), or diffusion times), combining the individual diffusion signals to determine a processed diffusion signal corresponding to at least one location within one or more voxels of the MRI data, calculating one or more parameters from the processed diffusion signal by using the diffusion weighting conditions, and using the one or more parameters to identify a characteristic of the biological structure, in which the one or more parameters include values over a range of one or more diffusion length scales based on at least one of diffusion distance or diffusion rate.

Measuring biological tissue parameters using diffusion magnetic resonance imaging

Methods, systems, and devices for automated analysis of medical scans

Systems, apparatus and methods that use a hidden Markov model to estimate motion of a sample under measurement and to reduce a motion-induced effect in the measurement. MRI systems and other sample measurement systems can be implemented based on motion sensing using the hidden Markov model. Recursive and non-recursive estimation processes are described.

Growing community of inventors

San Diego, CA, United States of America

Nathan S White