Clarius Mobile Health Corp.

Ultrasonix Medical Corporation

Analogic Canada Corporation

Other

Bk Medical Holding Company, Inc.

Clartus Mobile Health Corp.

Bk Medical Aps

Kris Dickie

Laurent Pelissier

Trevor Stephen Hansen

Nishant Uniyal

Benjamin Eric Kerby

Narges Afsham

Bo Zhuang

Parisa Asgharzadeh

Kwun-Keat Chan

Reza Zahiri

Corina Leung

Binda Zhang

Daniel Christian Rahardja

Siavash Khallaghi

David Glenn Willis

Jing Cheng

Michelle Alexander

Eric Fattah

Julien Lemaitre

Simon Dahonick

Jacob Ruben Barrera Loredo

Matt Potma

Wasiu Raimi

Chris Cheung

Reza Azar

An apparatus and method for generating high quality, high frame rate images in a handheld or hand-carried ultrasonic imaging machine. The apparatus includes an image enhancer to reduce speckle noise and improve the compressibility of the resulting image. This approach reduces the required hardware and power consumption to satisfy the physical space, power, and limited processing power of a handheld probe and enables high quality images to be transmitted efficiently over low-bandwidth connections.

Speckle reduction and compression improvement of ultrasound images

A method for automatically measuring a bladder on an ultrasound image feed, acquired from an ultrasound scanner comprises displaying, on a screen that is communicatively connected to the ultrasound scanner, the ultrasound image feed comprising ultrasound image frames of a bladder; deploying an AI model to execute on a computing device communicably connected to the ultrasound scanner, wherein the AI model is trained so that when the AI model is deployed, the computing device identifies and predicts a view of the bladder, from one of a sagittal view and a transverse view; acquiring, at the computing device, a new ultrasound image during ultrasound scanning; processing, using the AI model, the new ultrasound image to identify and predict the view of the bladder, wherein the prediction is an AI model output; wherein if f the AI model output predicts that the new ultrasound image comprises a sagittal view of the bladder, automatically applying one caliper set along a superior-inferior dimension of the bladder and measuring the superior-inferior dimension; and wherein if the AI model output predicts that the new ultrasound image comprises a transverse view of the bladder, applying two caliper sets along each of a length and a width of the bladder and measuring the length and width thereof.

Systems and methods for automated bladder measurement

A method for positioning one or both of a gate and a color box on an ultrasound image generated during scanning of an anatomical feature using an ultrasound scanner comprises deploying an artificial intelligence (AI) model to execute on a computing device communicably connected to the ultrasound scanner, wherein the AI model is trained so that when the AI model is deployed, the computing device generates a prediction of at least one of an optimal position, size, or angle for the gate and/or an optimal location/size of the color box on the ultrasound image generated during ultrasound scanning of the anatomical feature, thereafter enabling the acquisition of corresponding Doppler mode signals.

Systems and methods for placing a gate and/or a color box during ultrasound imaging

The present embodiments relate generally to ultrasound imaging systems and methods that provide, upon receipt of input of a tap gesture at a location directly on the ultrasound image feed on the touchscreen display, such location indicating on the post scan converted ultrasound image frame a desired focal adjustment point, the processor causes the ultrasound imaging system to i) revert the post scan converted ultrasound image frame comprising the location of the desired focal adjustment point, by way of the cartesian co-ordinates, to its corresponding pre-scan raw ultrasound data frame; ii) calculate, on the pre-scan raw ultrasound data frame, the location of the desired focal adjustment point, by way of polar co-ordinates of the desired focal adjustment point; and iii) adjust at least one beamformer parameter of ultrasound signals being used to transmit and receive the ultrasound image to focus at the desired focal adjustment point, based upon the polar coordinates.

Ultrasound systems and methods for user interface on image touchscreen control of focal zone adjustments

The present embodiments relate generally to methods for providing viewing access to an ultrasound image feed generated at an ultrasound imaging machine. A multi-use display device may form a first link-layer connection with the ultrasound image machine for transmitting commands that control imaging parameters of the ultrasound image feed. The multi-use display device may then: determine link-layer connection parameters that allow the ultrasound imaging machine to form a second link-layer connection with a receiving device (the receiving device having no link-layer connection with the ultrasound imaging machine), and provide the connection parameters to the receiving device. The ultrasound imaging machine forms a second link-layer connection with the receiving device, based the connection parameters. The second link-layer connection is then used for receiving, at the receiving device, the ultrasound image feed controlled by the multi-use display device.

Systems and methods of establishing a secondary connection at an ultrasound imaging machine, for providing access to an ultrasound image feed

The present embodiments relate generally to ultrasound imaging systems and methods that provide a user interface on the touchscreen display. The user interface includes an ultrasound image feed and a single control for modifying imaging depth of the ultrasound image feed. When input via the single control is received to modify the imaging depth, the system: adjusts frequency of ultrasound signals being used to acquire the ultrasound image feed; adjusts a beamformer parameter of the ultrasound signals being used to acquire the ultrasound image feed; receives first image data of the ultrasound image feed based on the adjusted frequency and the adjusted beamformer parameter; based on the first image data, adjusts Time Gain Compensation (TGC) of the ultrasound image feed; and receives second image data of the ultrasound image feed based on the adjusted frequency, beamformer parameter and TGC. Display of the second image data on the touchscreen display is then optimized without receipt of additional user input.

Ultrasound systems and methods for optimizing multiple imaging parameters using a single user interface control

A method of creating a 3D model, which is a visual representation of at least one physiological parameter, the method comprises deploying an AI model to execute on a computing device communicably connected to a medical imaging device, said medical imaging device acquiring medical imaging data, wherein the AI model is trained so that when it is deployed, the computing device identifies at least one physiological parameter from medical imaging data; acquiring, at the computing device, new medical imaging data; processing, using the AI model, the new medical imaging data to identify at least one physiological parameter (the 'at least one identified physiological parameter'); employing the at least one identified physiological parameter to select a corresponding 3D model; and modifying the corresponding 3D model to alter one or more model parameters therein, to match the at least one identified physiological parameter, thereby customizing the visual appearance of the corresponding 3D model.

Systems and methods for rendering models based on medical imaging data

A method and system provide for the identification of a tendon in ultrasound imaging data, by deploying an artificial intelligence (AI) model to execute on a computing device, wherein the AI model is trained to identify a plurality of different types of tendons imaged in ultrasound imaging data, and when deployed, the computing device generates a probability for each of the plurality of different types of tendons that the type of tendon is imaged in new ultrasound imaging data and wherein such probability is corroborated by at least one live deployment input.

Method and system for identifying a tendon in ultrasound imaging data and verifying such identity in live deployment

Post-scan ultrasound images are masked and labeled with anatomical features identified in the images. Masks corresponding to the features are transformed into the coordinate system of the pre-scan, raw ultrasound data frames corresponding to the images. The masks and their respective raw ultrasound data frames are used to train an artificial intelligence model. The model is then used to predict the presence of anatomical features of the same type in other pre-scan ultrasound data. Once predicted, the raw data is scan converted for display as segmented ultrasound images that identify the predicted anatomical features. Deployment of the model on pre-scan data avoids the need to account for different levels of processing that may be applied to post-scan images, while the labeling for training the model may be done on the post-scan images.

Method and system for training and deploying an artificial intelligence model on pre-scan converted ultrasound image data

Systems and methods for providing an interactive demonstration of an ultrasound user interface are generally described herein. The method may include, at a multi-use display device: receiving a demonstration ultrasound dataset from a server; displaying, on the ultrasound user interface, ultrasound data from the demonstration ultrasound dataset; receiving input, on the ultrasound user interface, to interact with the ultrasound data from the ultrasound dataset; and in response to the received input, updating the ultrasound user interface so that the ultrasound user interface corresponds to the received input, the updated ultrasound user interface appearing substantially similar to an appearance of the ultrasound user interface that is displayed if the received input is received during display of a live ultrasound image feed.

Systems and methods for providing an interactive demonstration of an ultrasound user interface

An ultrasound imaging system including an ultrasound imaging apparatus operable to acquire ultrasound image data and an add-on vibration inducing device operable to generate shear waves. The add-on vibration inducing device is connected cordlessly to the ultrasound imaging apparatus. The add-on vibration inducing device can be powered and controlled by the ultrasound imaging apparatus. The add-on vibration inducing device includes a connector to scanner which connects cordlessly to a power connector on the ultrasound imaging apparatus for transmitting the power and the control signals from the ultrasound imaging apparatus to the add-on vibration inducing device. The ultrasound imaging apparatus can be used separately from the add-on vibration inducing device for ultrasound imaging procedures and the add-on vibration inducing device can be easily mounted on the ultrasound imaging apparatus when the user wishes to perform an elastography diagnostic procedure.

Ultrasound imaging apparatus with an add-on vibration inducing device for ultrasound elastography

A method and system for assessing medical images for suitability in clinical interpretation is described herein. The method and system involve: acquiring a medical image; inputting the medical image into a machine learning model, wherein the machine learning model is configured to determine a quality value based on the medical image; determining whether the quality value meets a quality threshold associated with a target clinical application; and when the quality value meets the quality threshold associated with the target clinical application, permitting clinical interpretation of the medical image for the target clinical application.

Method and system to assess medical images for suitability in clinical interpretation

During acquisition of an ultrasound image feed, ultrasound control data frames are acquired that may be interspersed amongst the ultrasound data frames. The control data frames may use consistent reference scan parameters, irrespective of the scanner settings, and may not need to be converted to image frames. The control data frames can be passed to an artificial intelligence model, which predicts the suitable settings for scanning the anatomy that is being scanned. The artificial intelligence model can be trained with a dataset containing different classes of ultrasound control data frames for different settings, where substantially all the ultrasound control data frames in the dataset are consistently acquired using the reference scan parameters.

Method and system for controlling settings of an ultrasound scanner

An ultrasound imaging system comprising a multi-use electronic display device and an ultrasound imaging device. The multi-use electronic display device is capable of communicating with one or more ultrasound imaging devices and selecting which to connect with based on at least one of previously store information, user input, and information gathered from the ultrasound imaging devices. The multi-use electronic display device may communicate with the ultrasound imaging devices while they are in a low power standby state. This approach reduces the complexity of the pairing process and provides a means for quickly and easily selecting between multiple ultrasound imaging devices.

System and method for locating an ultrasound imaging device from a multi-use electronic display device

Ultrasound images are adjusted according to the size of the display area available to display them, so that image detail is displayed with a large enough physical size to discern comfortably. A translation ratio is determined for translating the physical distance traversed by the ultrasound signals of an ultrasound images to a corresponding physical distance on a screen of the display device. If the ratio is not below a threshold, the image is displayed in full. If the ratio is below the threshold, the image is cropped, optionally scaled, and displayed in the available area. Scaling and cropping may be based on window size and threshold window size. The parameters of the ultrasound scan may be controlled based on the scaling, cropping, or available screen size. User interface features may be displayed on the screen depending on how much area is available when the image is displayed.

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Vancouver, Canada

Kris Dickie