Abstract: Examples of the present disclosure describe systems and methods for implementing real-time artificial intelligence (AI) for physical biopsy marker detection. In aspects, the physical characteristics for one or more biopsy site markers may be used to train an AI component of an ultrasound system. The trained AI may be configured to identify deployed markers. When information relating to the characteristics of a deployed marker is input into the ultrasound system, the trained AI may process the received information to create one or more estimated images of the marker, or identify echogenic properties of the marker. During an ultrasound of the site comprising the deployed marker, the AI may use the estimated images and/or identified properties to detect the shape and location of the deployed marker.

Abstract: Examples relate to a method for processing beamformed data of a medium. The beamformed data includes a first set of beamformed data associated with a first spatial region and a second set of beamformed data associated with a second spatial region, and the method includes estimating the clutter caused by the second spatial region at the first set.

Abstract: A method for estimating an ultrasonic attenuation parameter of a region in a medium includes a transmission step in which at least one pulse is transmitted in the medium by a transducer, and a reception step in which data is acquired by a transducer in response to the pulse. The method includes a processing step in which the data is processed by the processing unit for providing backscattered acquisition data of the region, and a function determination step in which an auto-correlation function of the backscattered acquisition data is determined which is a function of depth in the spatio-temporal domain, the autocorrelation function being determined at a lag of zero. The method includes an attenuation estimation step in which an ultrasonic attenuation parameter is estimated based on said auto-correlation function. The method is implemented by a processing unit associated to at least one ultrasound transducer.

Abstract: Examples relate to a method for processing beamformed data of a medium. The beamformed data includes a first set of beamformed data associated with a first spatial region and a second set of beamformed data associated with a second spatial region, and the method includes estimating the clutter caused by the second spatial region at the first set.

Abstract: Examples relate to a method for processing beamformed data of a medium. The beamformed data includes a first set of beamformed data associated with a first spatial region and a second set of beamformed data associated with a second spatial region, and the method includes estimating the clutter caused by the second spatial region at the first set.

Abstract: The disclosure relates to a method of linking ultrasound image data associated with a medium with other image data associated with the medium. The method comprises: estimating deformability properties of the medium based on the ultrasound data and linking the ultrasound image data with the other image data based on the deformability properties.

Abstract: Examples relate to a method for processing beamformed data of a medium. The beamformed data includes a first set of beamformed data associated with a first spatial region and a second set of beamformed data associated with a second spatial region, and the method includes estimating the clutter caused by the second spatial region at the first set.

Abstract: Methods and systems for identifying a region of interest in breast tissue utilize artificial intelligence to confirm that a target lesion identified during imaging the breast tissue using a first imaging modality (e.g. x-ray imaging) has been identified using a second imaging modality (e.g. ultrasound imaging). A computing system operating a lesion matching engine utilizes a machine learning classifier algorithm trained on cases of x-ray images and corresponding ultrasound images in which lesions were identified for further analysis. The lesion matching engine analyzes a target lesion identified with x-ray imaging and a potential lesion identified with ultrasound imaging to determine a likelihood that the target lesion is the same as the potential lesion. A confidence level indicator for the lesion match is presented on a display of a computing device to aid a healthcare provider in locating a lesion in breast tissue.

Abstract: Examples of the present disclosure describe systems and methods for implementing real-time artificial intelligence (AI) for physical biopsy marker detection. In aspects, the physical characteristics for one or more biopsy site markers may be used to train an AI component of an ultrasound system. The trained AI may be configured to identify deployed markers. When information relating to the characteristics of a deployed marker is input into the ultrasound system, the trained AI may process the received information to create one or more estimated images of the marker, or identify echogenic properties of the marker. During an ultrasound of the site comprising the deployed marker, the AI may use the estimated images and/or identified properties to detect the shape and location of the deployed marker.

Abstract: The invention relates to a method for processing a set of signals of a transducer device comprising a respective set of transducer elements, the method comprising the following steps: a processing step in which the received set of signals is processed to a plurality of synthetic waves, and an output step in which the plurality of synthetic waves is outputted through a plurality of channels.

Abstract: Systems and methods for mapping a region of interest within breast tissue utilize multiple layers of information to produce a unique digital fingerprint of breast tissue. X-ray and ultrasound imaging is combined with elastography and Doppler to create an architectural map of a breast including coordinates to mark one or more regions of interest. The architectural map can be utilized during future imaging procedures and surgeries to automatically and virtually indicate the location of previously biopsied lesions. The architectural map can be displayed on a user interface of a computing device to guide a user to the region of interest during imaging.

Abstract: Disclosed is an imaging method for producing an image of a region inside a medium by an array of transducers, including the a transmission step of a plurality of waves inside the medium, a reception step for acquiring a set of data, a beamforming step providing a plurality beamformed pixel values depending on various transmit weighting vectors, and a combining step for combining the beamformed pixel values into a pixel value of each pixel in the image. The transmit weighting vectors are different and orthogonal one to another one.

Abstract: A method for compensating a depth-dependent attenuation in ultrasonic signal data of a medium and a system for performing the method. The method is implemented by a processing system (8), the method comprising the following: processing (c), in which ultrasound signal data is processed by the processing unit for providing in-phase and quadrature phase (IQ) data of the medium, and attenuation compensation (f), in which a phase of the IQ data is compensated as a function of a respective frequency shift amount for each of a plurality of different depths (z1, z2, zn) in the medium, such that the IQ data spectrum is recentered across the plurality of different depths.

Abstract: A method for estimating an ultrasonic attenuation parameter of a region in a medium includes a transmission step in which at least one pulse is transmitted in the medium by a transducer, and a reception step in which data is acquired by a transducer in response to the pulse. The method includes a processing step in which the data is processed by the processing unit for providing backscattered acquisition data of the region, and a function determination step in which an auto-correlation function of the backscattered acquisition data is determined which is a function of depth in the spatio-temporal domain, the autocorrelation function being determined at a lag of zero. The method includes an attenuation estimation step in which an ultrasonic attenuation parameter is estimated based on said auto-correlation function. The method is implemented by a processing unit associated to at least one ultrasound transducer.

Abstract: Disclosed is an imaging method for producing an image of a region inside a medium by an array of transducers, including the a transmission step of a plurality of waves inside the medium, a reception step for acquiring a set of data, a beamforming step providing a plurality beamformed pixel values depending on various transmit weighting vectors, and a combining step for combining the beamformed pixel values into a pixel value of each pixel in the image. The transmit weighting vectors are different and orthogonal one to another one.

Abstract: The disclosure includes a method of acquiring high-resolution ultrasound images using an array of transducers using successive transmission matrices.

Abstract: The disclosure includes a method of acquiring high-resolution ultrasound images using an array of transducers using successive transmission matrices.

Abstract: A device for decoding a direct sequence spread spectrum-encoded binary message includes a sampler that captures at least one sequence of binary samples corresponding to one bit of the transmitted message. The captured sequence of samples are applied to a filter matched to the spreading code used, thus making it possible to delete the spreading applied to the original message. The device further includes, at the output of the sampler, an error correction block including a memory storing a plurality of binary sequences corresponding to all of the possible values for a captured sequence of samples. A replacement circuit replaces the captured sequence of samples with the stored sequence, thereby minimizing the number of samples different from the captured sequence of samples, and allowing the stored sequence to be applied to the matched filter.

Abstract: The invention relates to a decoding device particularly adapted to decode a digital input signal (E) in a transmission system using direct sequence spread spectrum, this digital input signal (E) being composed of symbols, each symbol representing a bit satisfying a Barker code, and comprising several symbol elements. This device comprises several finite response filters (FLT1 to FLT4) each of which receives the digital input signal (E), a clock circuit (CLK_GEN) outputting clock signals (CLK1 to CLK4) to the filters with a frequency equal to the frequency at which symbol elements are produced and uniformly distributed phase shifts, and an analysis circuit (ANL) designed to identify which of the filters is best tuned to the input signal (E) and to control the clock circuit to make it generated a clock signal (CLK5) optimised for decoding and an analysis circuit.

Abstract: A receiver device for a modulated signal, suited in particular to a transmission system using a binary carrier phase modulation by means of a binary message on which a direct sequence spread spectrum operation has been carried out, this device comprising a first analog radio frequency part, transforming the signal received into a low-frequency, demodulated signal, said demodulated signal being applied to a second digital part of said device comprising an analog-to-digital converter and a filter matched to the spreading code used in order to delete the spreading applied to the original message, said device being characterized in that it includes an additional filtering unit, arranged between the analog-to-digital converter and the matched filter, said filtering unit implementing a stochastic matched filtering operation in order to improve the signal-to-noise ratio at the input of said matched filter.