Other

Imris, Inc.

Sightline Innovation Inc.

Mark Alexiuk

Wallace Trenholm

Maithili Mavinkurve

Jason Cassidy

Siavash Malektaji

Kamal Darchinimaragheh

Hieu Dang

Gordon Scarth

Wayne Schellekens

Stephen G Hushek

Mehran Fallah-Rad

Meir Dahan

Kirk Champagne

Michael Lang

Vlajko Srzic

Timothy James Hoeppner

Labros Petropolous

David John Robert Weber

Wayne Theodore Schellekens

Viajko Srzic

A system and method for non-destructive optical coherence tomography (OCT) is provided. The system includes: an input interface for receiving OCT data including at least a C-scan; a processing unit executable to detect a feature on a surface or subsurface of the object, trained using a training set and configured to: separate the C-scan into A-scans; using a neural network, successively analyze each A-scan to detect the presence of an A-scan feature associated with the object; separate the C-scan into B-scans; segment each of the B-scans to determine thresholds associated with the object; using a neural network, successively analyze each segmented B-scan to detect the presence of an B-scan feature associated with the object; convert the C-scan to one or more two-dimensional representations; and using a neural network, detect the presence of an C-scan feature associated with the object.

Neural network system for non-destructive optical coherence tomography

A method and system for increasing data quality of a dataset for semi-supervised machine learning analysis. The method includes: receiving known class label information for a portion of the data in the dataset; receiving clustering parameters from a user; determining a data cleanliness factor, and where the data cleanliness factor is below a predetermined cleanliness threshold: assigning data without class label information as a data point to a cluster using the clustering parameters, each cluster having a cluster class label associated with such cluster; and determining a measure of assignment, and where the measure of assignment for each data point is below a predetermined assignment threshold, receiving a class label for such data points, otherwise, assigning the respective cluster class label to each data point with the respective measure of assignment below the predetermined assignment threshold; and otherwise, outputting the dataset with associated class labels for machine learning analysis.

System and method for increasing data quality in a machine learning process

Embodiments described herein relate to systems and methods for specular surface inspection, and particularly to systems and methods for surface inspection comprising inverse synthetic aperture imaging ('ISAI') and specular surface geometry imaging ('SSGI'). Embodiments may allow an object under inspection, to be observed, imaged and processed while continuing to be in motion. Further, multiple optical input sources may be provided, such that the object does not have to be in full view of all optical sensors at once. Further, multi-stage surface inspection may be provided, wherein an object under inspection may be inspected at multiple stages of an inspection system, such as, for an automotive painting process, inspection at primer, inspection at paint, inspection at final assembly. SSGI imaging modules are also described for carrying out micro-deflectometry.

System and method for specular surface inspection

An application provisioning system and method. A server provides an application provisioning service. A user of a client provides a schema defining an application. The application interacts with peripherals coupled to the client and receives input from sensors coupled to the peripherals. The sensor data is provided to the server for processing, including by neural networks. The application includes a workflow defining a finite state machine that traverses states at least partially based on the response to sensor data. The server may provide dynamic reallocation of compute resources to resolve demand for classifier training job requests; use of jurisdictional certificates to define data usage and sharing; and data fusion. Applications include manufacturing verification, medical diagnosis and treatment, genomics and viral detection.

System and method for applying a deep learning neural network to data obtained from one or more sensors

For use in MR imaging of a patient a plurality of surface electrodes such as ECG or defibrillator are provided for obtaining electrical signals for determining electrical activity within the body of the patient and remain in place during the MR imaging. The surface electrodes include a quick disconnect wire for carrying the signals to a signal processing system to be removed during the MR imaging to prevent heating. Each electrode comprises a conductive layer divided by slits into separate side by side sections to reduce eddy currents which are induced in the surface electrodes when they are exposed to variations in the magnetic field. The sections all are connected through the layer to the conductive location to allow the signal therefrom to be connected to the communication conductor.

Surface electrode design that can be left in place during MR imaging

In MR imaging in a suite of rooms including a diagnostic room and a second surgical room, the magnet includes a diagnostic table separable from a docking station of the magnet and the second room includes a second surgical table. An imaging control computer controls operation of the imaging system and a movement control computer controls operation of the magnet moving system and the patient support table. During imaging in the surgical room, the diagnostic table is separated and docked at a secondary docking station while an emulating computer system cooperate with the imaging control computer system by emulating outputs from the disconnected diagnostic table for controlling operation of the imaging system.

MR imaging in separate rooms using a magnet having a diagnostic table

In a MRI system housed within a room there is provided a movable magnet and additional components for other procedures on the patient, a control system is provided for the relative movement of the magnet and components. This includes a plurality of magnetic field sensors mounted on the components for measuring the magnetic field at the location of the component and an optional camera positioning system so that the control system can estimate relative positions of the components relative to the magnet from the sensed field strengths from the set of sensors to avoid collisions during the movements.

MRI safety system

Growing community of inventors

Winnipeg, Canada

Mark Alexiuk