Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Devices, systems, and methods are provided in which noise or artifacts generated by motion of a probe are attenuated in acquired physiological data, such as auscultation or ultrasound data. One such method includes acquiring physiological data of a patient by a handheld device. Motion of the handheld device is sensed, and a determination is made as to whether the sensed motion of the handheld device exceeds a motion threshold. The method further includes generating conditioned physiological data of the patient by attenuating a portion of the acquired physiological data in response to determining that the sensed motion of the handheld device exceeds the motion threshold.

Abstract: Ultrasound image recognition systems and methods, and artificial intelligence training networks for such systems and methods, are provided. An ultrasound data information system includes an ultrasound image recognition training network that is configured to receive ultrasound training images and to develop ultrasound image knowledge based on the received ultrasound training images. An ultrasound imaging device acquires ultrasound images of a patient, and the device includes an ultrasound image recognition module. The ultrasound image recognition module is configured to receive the ultrasound image knowledge, receive the acquired ultrasound images from the ultrasound imaging device, and determine, based on the ultrasound image knowledge, whether the received ultrasound images represent a clinically desirable view of an organ or whether the clinically desirable views indicate normal function or a particular pathology.

Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Ultrasound image recognition systems and methods, and artificial intelligence training networks for such systems and methods, are provided. An ultrasound data information system includes an ultrasound image recognition training network that is configured to receive ultrasound training images and to develop ultrasound image knowledge based on the received ultrasound training images. An ultrasound imaging device acquires ultrasound images of a patient, and the device includes an ultrasound image recognition module. The ultrasound image recognition module is configured to receive the ultrasound image knowledge, receive the acquired ultrasound images from the ultrasound imaging device, and determine, based on the ultrasound image knowledge, whether the received ultrasound images represent a clinically desirable view of an organ or whether the clinically desirable views indicate normal function or a particular pathology.

Abstract: Automated ultrasound image labeling and quality grading systems and methods are provided. An ultrasound system includes an ultrasound imaging device configured to acquire ultrasound images of a patient. An anatomical structure recognition and labeling module receives the acquired ultrasound images from the ultrasound imaging device, and automatically recognizes anatomical structures in the received ultrasound images. The anatomical structure recognition and labeling module automatically labels the anatomical structures in the images with information that identifies the anatomical structures. The acquired ultrasound images and the labeled anatomical structures are displayed on a display of the ultrasound imaging device.

Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Systems and methods for controlling parameters associated with ultrasound images displayed on a computing device, based on sensed motion of the computing device, are provided herein. One such system includes an ultrasound probe and a computing device coupled to the ultrasound probe and operable to receive ultrasound signals from the ultrasound probe. The computing device includes a motion sensor that senses motion of the computing device, a display that displays ultrasound images associated with the ultrasound signals received from the ultrasound probe, and an image display controller that controls at least one parameter associated with the displayed ultrasound images based on the sensed motion.

Abstract: Systems, methods and devices for providing combined ultrasound, electrocardiography, and auscultation data are provided. One such system includes an ultrasound sensor, an electrocardiogram (EKG) sensor, an auscultation sensor, and a computing device. The computing device includes memory and a processor, and the processor receives signals from the ultrasound sensor, the EKG sensor, and the auscultation sensor. Artificial intelligence techniques may be employed for automatically analyzing the data obtained from the ultrasound sensor, the EKG sensor, and the auscultation sensor and producing a clinically-relevant determination based on a combined analysis of the data.

Abstract: Ultrasound image recognition systems and methods, and artificial intelligence training networks for such systems and methods, are provided. An ultrasound data information system includes an ultrasound image recognition training network that is configured to receive ultrasound training images and to develop ultrasound image knowledge based on the received ultrasound training images. An ultrasound imaging device acquires ultrasound images of a patient, and the device includes an ultrasound image recognition module. The ultrasound image recognition module is configured to receive the ultrasound image knowledge, receive the acquired ultrasound images from the ultrasound imaging device, and determine, based on the ultrasound image knowledge, whether the received ultrasound images represent a clinically desirable view of an organ or whether the clinically desirable views indicate normal function or a particular pathology.

Abstract: The present disclosure is directed to systems and methods which avow for ultrasound parameter estimation to occur at specific advantageous sets of points in a two- or three-dimensional field of view within re-configurable, massively parallel, programmable architectures that can accommodate the input/output streaming, data movement or storage, and computation requirements. In one embodiment, a power efficient system is used for processing the data thereby increasing the ability of the system to be used for hand carried or mobile ultrasound applications. One aspect of the concepts discussed herein is the architectural aspects which provide the ability to simultaneously accept a large number of channels of data characterized by a continuous, simultaneous flow at high sample rates. The input data is routed at high rates to a distributed and large number of processing elements, memory, and connections for simultaneous parameter estimation at multiple points in the field of view.

Abstract: A system performs ultrasound parameter estimation at specific advantageous sets of points in a two- or three-dimensional field of view within re-configurable, massively parallel, programmable architectures. A power efficient system is used for processing the data, thereby increasing the ability of the system for mobile ultrasound applications. Various architectural aspects provide the ability to simultaneously accept a large number of channels of data characterized by a continuous, simultaneous flow at high sample rates. The input data is routed at high rates to a distributed and large number of processing elements, memory, and connections for simultaneous parameter estimation at multiple points in the field of view, thereby enabling data streaming through the architecture.

Abstract: A system comprises an application specific integrated circuit (ASIC) adapted for use in a plurality of circuit configurations. The circuit configurations provide for different numbers of signal channels for further processing using same circuitry of said application specific integrated circuit.

Abstract: The present invention is directed to a system and method which makes a phased array look like a curved array for purposes of performing spatial compounding calculations. In one embodiment, the phased array is treated as though it were a curved array by creating both a virtual apex and a virtual radius of curvature. Based on this transformation, standard spatial-compounding resampling tables can be used just as they are with curved arrays. In one embodiment, after the data is compounded to form the target image, certain data is removed prior to the actual display. This removed data represents data generated by virtual rays the prior to the physical skin line of the phased array.

Abstract: A handheld ultrasound instrument is disclosed having enhanced diagnostic modes including pulse/continuous wave Doppler, time-motion analysis, spectral analysis and tissue harmonic imaging. An external electrocardiograph (ECG) recording unit is also disclosed. The ECG unit is adaptable to be used with the handheld ultrasound instrument to provide for ECG monitoring while performing an ultrasound scan in B-mode, Doppler, color Doppler, M-mode, and CW/PW mode. The enhanced handheld ultrasound instrument further includes a security mechanism allowing any combination of the diagnostic modes to be enabled by the manufacturer, and later to enable or disable any one or group of the diagnostic modes. The invention also discloses a method for a manufacturer to maintain a database of handheld ultrasound instrument capabilities after the instruments enter the stream of commerce.

Abstract: The present invention is directed to a system and method which makes a phased array look like a curved array for purposes of performing spatial compounding calculations. In one embodiment, the phased array is treated as though it were a curved array by creating both a virtual apex and a virtual radius of curvature. Based on this transformation, standard spatial-compounding resampling tables can be used just as they are with curved arrays. In one embodiment, after the data is compounded to form the target image, certain data is removed prior to the actual display. This removed data represents data generated by virtual rays the prior to the physical skin line of the phased array.

Abstract: The present disclosure is directed to systems and methods which allow for ultrasound parameter estimation to occur at specific advantageous sets of points in a two- or three-dimensional field of view within re-configurable, massively parallel, programmable architectures that can accommodate the input/output streaming, data movement or storage, and computation requirements. In one embodiment, a power efficient system is used for processing the data thereby increasing the ability of the system to be used for hand carried or mobile ultrasound applications. One aspect of the concepts discussed herein is the architectural aspects which provide the ability to simultaneously accept a large number of channels of data characterized by a continuous, simultaneous flow at high sample rates. The input data is routed at high rates to a distributed and large number of processing elements, memory, and connections for simultaneous parameter estimation at multiple points in the field of view.

Abstract: Systems and methods which analyze an image and extract features of the image therefrom for use in filtering are shown. Based on the features and structures, embodiments determine how to filter at different orientations and with different filter configurations. Filters utilized according to embodiments are adaptive with respect to spatial and/or temporal aspects of the features. Image processing according to embodiments is performed on sub-images at various levels of resolution.