Patent classifications
A61B8/52
METHOD, APPARATUS, AND SYSTEM FOR ADJUSTING BRIGHTNESS OF ULTRASOUND IMAGE BY USING PRESTORED GRADATION DATA AND IMAGES
Provided is a method of adjusting brightness of an ultrasound image including: generating at least one first image representing a region of interest (ROI) by using echo signals corresponding to ultrasound waves irradiated toward the ROI; adjusting brightness of the at least one first image based on an external signal for selecting at least one selected from a plurality of prestored gradation data and a plurality of prestored image data; and generating a second image representing the ROI based on the adjusted brightness.
ANATOMICALLY INTELLIGENT ECHOCARDIOGRAPHY FOR POINT-OF-CARE
An apparatus includes an imaging probe and is configured for dynamically arranging presentation of visual feedback for guiding manual adjustment, via the probe, of a location, and orientation, associated with the probe. The arranging is selectively based on comparisons between fields of view of the probe and respective results of segmenting image data acquired via the probe. In an embodiment, the feedback does not include a grayscale depiction of the image data. Coordinate system transformations corresponding to respective comparisons may be computed. The selecting may be based upon and dynamically responsive to content of imaging being dynamically acquired via the probe.
FOCUS TRACKING IN ULTRASOUND SYSTEM FOR DEVICE TRACKING
An ultrasound system includes an ultrasound probe (205) and an image processor (202) for generating ultrasound images from acoustic data received by the probe, and for automatically making adjustments to beamformed acoustic pulse locations and deriving the adjustments to the pulse locations from pre-established user image adjustment selections available on a user interface. A relationship is established between a depth of a distal end (231) of a medical device (230) and a transmit focal depth displayed on a display (300). A depth of the distal end of the medical device (230) is used to generate increment/decrement decisions with respect to a transmit focal depth.
Ultrasonic Diagnosis Device and Electronic Circuit
An electronic circuit in an ultrasonic probe includes a plurality of sub beamformers and a control unit. Each sub beamformer includes M delay circuits and an adding circuit. Each delay circuit includes a memory cell array which is formed of N memory cells. Conditions of cyclic operations of the M memory cell arrays (for example, timings of start triggers) are made irregular, such that use starting stage numbers in the M memory cell arrays are different.
Method, apparatus, and system for adjusting brightness of ultrasound image by using prestored gradation data and images
Provided is a method of adjusting brightness of an ultrasound image including: generating at least one first image representing a region of interest (ROI) by using echo signals corresponding to ultrasound waves irradiated toward the ROI; adjusting brightness of the at least one first image based on an external signal for selecting at least one selected from a plurality of prestored gradation data and a plurality of prestored image data; and generating a second image representing the ROI based on the adjusted brightness.
Method for the detection and quantification of conductance of right-to-left cardiac shunts
A system for detecting/quantifying the conductance of a right-to-left cardiac shunt includes a mouthpiece assembly, a solenoid-driven vacuum/pressurization assembly; a controller for operating the solenoid-driven vacuum/pressurization assembly; and a monitor for displaying the instructions from the controller. A microbubble counting cell and digital image sensor are combined with software-based image analysis to determine a number of microbubbles contained in a microbubble counting zone. A monitor enables operator specification of total volume of contrast agent to be injected into the patient. One or more first Doppler ultrasound transducer arrays are positioned adjacent to targeted intracranial arteries at one side of the skull or a pair of first Doppler ultrasound transducer arrays positioned adjacent to targeted intracranial arteries at both sides of the skull. A second Doppler ultrasound transducer is positioned on the precordium of the patient to detect the arrival of microbubble-containing contrast agent in the right atrium of the patient.
ULTRASONIC IMAGING WITH CLUTTER FILTERING FOR PERFUSION
Described herein are methods and apparatus for increasing sensitivity of ultrasound imaging of fluid flow in an object of interest. Ultrasound imaging of blood perfusion can be performed without contrast enhancement. Embodiments include transforming a spatiotemporal echo data array into a three-dimensional perfusion data array having a spatial dimension, a slow-time dimension, and a frame-time dimension, and filtering the perfusion data array with an eigen passband clutter filter. The clutter filter can increase sensitivity and utility of ultrasound imaging of fluid flow. In some aspects, the method can yield blood flow signal power and perfusion values well separated from tissue clutter. In an example, enhancements to ischemic tissue perfusion maps in a murine model are shown.
Automated image analysis for diagnosing a medical condition
Aspects of the technology described herein relate to techniques for guiding an operator to use an ultrasound device. Thereby, operators with little or no experience operating ultrasound devices may capture medically relevant ultrasound images and/or interpret the contents of the obtained ultrasound images. For example, some of the techniques disclosed herein may be used to identify a particular anatomical view of a subject to image with an ultrasound device, guide an operator of the ultrasound device to capture an ultrasound image of the subject that contains the particular anatomical view, and/or analyze the captured ultrasound image to identify medical information about the subject.
Automatic image vetting on a handheld medical scanning device
In an embodiment, an ultrasound scanning device is disclosed. One embodiment of the ultrasound scanning device comprises a housing configured for handheld use, an ultrasound assembly at least partially disposed within the housing and configured obtain ultrasound data, and a display coupled to the housing. The ultrasound scanning device further comprises a processor disposed within the housing, wherein the processor is in communication with the ultrasound assembly and the display. The processor is operable to receive a selection of a scanning procedure to be completed using the ultrasound assembly, receive ultrasound data from the ultrasound assembly, and filter the received ultrasound data, based on the scanning procedure, to segregate ultrasound data relevant to the scanning procedure from ultrasound data irrelevant to the scanning procedure, store the relevant ultrasound data, discard the irrelevant ultrasound data, and output a graphical representation associated with the relevant ultrasound data to the display.
Ultrasound-target-shape-guided sparse regularization to improve accuracy of diffused optical tomography and target depth-regularized reconstruction in diffuse optical tomography using ultrasound segmentation as prior information
A diffuse optical tomography (DOT) system for generating a functional image of a lesion region of a subject is described. The DOT system includes a source subsystem configured to generate optical waves, a probe coupled to the source subsystem and configured to emit the optical waves generated by the source subsystem toward the lesion region and to detect optical waves reflected by the lesion region, a detection subsystem configured to convert the optical waves detected by the probe to digital signals, and a computing device including a processor and a memory. The memory includes instructions that program the processor to receive the digital signals sent from the detection subsystem and perform reconstruction using a depth-regularized reconstruction algorithm combined with a semi-automated interactive convolutional neural network (CNN) for depth-dependent reconstruction of absorption distribution.