Delphinus Medical Technologies, Inc.

Qualcomm Incorporated

Ecole Polytechnique Federale De Lausanne

Olivier Roy

Cuiping Li

Nebojsa Duric

Steven Schmidt

Martin Vetterli

Peter John Littrup

Gursharan Singh Sandhu

Ivana Jovanovic

Erik West

Ali Hormati

Mark Sak

Yue M Lu

Neb Duric

Culping Li

A method of analyzing an image of a volume of tissue to determine a risk of developing breast cancer using a volume averaged sound speed within the volume. A method of determining a response to a treatment plan by determining a volume and a volume averaged sound speed of a region of interest within a volume of breast tissue and generating a combined metric from the volume and the volume averaged sound speed over the plurality of instances of time. A method of analyzing an image of a volume of tissue of a breast by applying a spatial filter to at least one ultrasound tomography image at the computing system and generating a stiffness map from the at least one ultrasound tomography image.

Methods and systems for cancer risk assessment using tissue sound speed and stiffness

A method and system for analyzing stiffness in a volume of tissue, the method including: emitting acoustic waveforms toward the volume of tissue with an array of ultrasound transmitters; detecting, with an array of ultrasound receivers, a set of acoustic signals derived from acoustic waveforms transmitted through the volume of tissue; generating, from the set of acoustic signals, a sound speed map and an acoustic attenuation map of a region of the volume of tissue, generating a stiffness map derived from combination of a set of sound speed parameter values of the sound speed map and a corresponding set of acoustic attenuation parameter values of the acoustic attenuation map, the stiffness map representing the distribution of the stiffness parameter across the region; and at a display in communication with the computer processor, rendering a stiffness image of the volume of tissue, based upon the stiffness map.

Method for representing tissue stiffness

This application presents a system and related methods that analyze a volume of tissue using ultrasound waveform tomography imaging. By using frequency-domain waveform tomography techniques and a gradient descent algorithm, the system can reconstruct the sound speed distributions of a volume of tissue, such as breast tissue, of varying densities with different types of lesions. By allowing sound speed to have an imaginary component that characterizes sound attenuation, the system can classify the different types of lesions with a fine granularity.

Tissue imaging and analysis using ultrasound waveform tomography

A method and system for generating an enhanced image of a volume of tissue, the method comprising: emitting acoustic waveforms toward the volume of tissue; detecting a set of acoustic signals derived from acoustic waveforms interacting with the volume of tissue; generating, from the set of acoustic signals, an initial model representing a distribution of an acoustomechanical parameter across a region of the volume of tissue; extracting a set of frequency components, from the set of acoustic signals; generating a first simulated wavefield with a first frequency component of the set of frequency components; generating an updated model of the initial model with the first simulated wavefield; iteratively refining the updated model with a set of simulated wavefields associated with the set of frequency components until a threshold condition is satisfied, thereby producing a final model; and generating the enhanced image from the final model of the volume of tissue.

Ultrasound waveform tomography method and system

A method and system for imaging a volume of tissue and defining a tissue boundary comprising: receiving a baseline dataset representative of a first set of signals interacting with a medium; receiving a reconstruction dataset representative of a second set of signals interacting with the medium and the volume of tissue present in the medium; determining a set of direct emitter-receiver pairs, each defining a direct trajectory that does not pass through the volume of tissue; from the set of direct emitter-receiver pairs, determining a set of tangential emitter-receiver pairs, each defining a bounding vector comprising a tangent point along the tissue boundary; determining a set of interior pixels, of the reconstruction dataset, characterized by a set of pixel locations within the tissue boundary; and reconstructing pixels of the set of interior pixels, thereby transforming the baseline and the reconstruction datasets into an image rendering of the volume of tissue.

Method and system for imaging a volume of tissue with tissue boundary detection

Certain aspects of the present disclosure provide methods for distributed sensing and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation.

Distributed sensing of signals linked by sparse filtering

A method for imaging a volume of tissue in a scan region, including: emitting, from transmitting transducers, acoustic waveforms toward the volume of tissue; detecting, with detecting transducers, a plurality acoustic signals derived from acoustic waveforms interacting with the volume of tissue; generating from the detected acoustic signals a plurality of variable attenuation maps, in which each variable attenuation map corresponds to acoustic signals detected by a respective detecting transducer and includes a plurality of variable attenuation coefficients mapped to the scan region; modifying at least a portion of the detected acoustic signals based on one or more variable attenuation maps; and generating a reflection rendering of the volume of tissue based on the modified acoustic signals.

Method for imaging a volume of tissue

An iterative method for calibrating a transducer array characterized by calibration parameters, based on time delay measurements between transducer pairs, comprising the steps of: creating a distance data set that includes pairwise distances between estimated positions of transducer; forming a time delay measurement data set that includes time delay measurements between transducer pairs; generating from the time delay measurement data set an estimate of at least one calibration parameter; modifying the time delay measurement data set and the distance data set based on the estimated calibration parameters; denoising the modified distance data set with an iterative algorithm; updating the estimated positions of transducers based on the denoised modified distance data set; and repeating at least a portion of the steps until the difference between the estimated positions of transducer pairs and updated estimated positions of transducers satisfies a stopping criterion.

Method for calibrating a transducer array

The aim of the invention is to provide inter-channel level differences ICLD related to audio signals for hearing aids. This aim is achieved by a method for computing ICLD from a first and second audio source signals, the first source signal being wired with a first processing module and the second source signal being wired with a second processing module, the second processing module receiving wirelessly information from the first processing module, this method comprising the steps of: acquiring first samples of the first sound signal by the first processing module, defining a first time frame, converting the first time frame into first frequency bands and grouping them into two first frequency sub-bands, calculating a first power estimate of each first frequency sub-bands, encoding and transmitting same to the second processing module, acquiring second samples of the second sound signal by the second processing module, defining a second time frame comprising acquired samples, converting same into second frequency bands, grouping them into two second frequency sub-bands, calculating a second power estimate of each second frequency sub-bands, receiving and decoding the encoded first power estimates, computing for each frequency sub-band, an ICLD by subtracting the first decoded power estimates and the second power estimates.

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Royal Oak, MI, United States of America

Olivier Roy