Acuson Corporation

Siemens Medical Solutions Usa, Inc.

Ismayil M Guracar

Patrick J Phillips

Samuel H Maslak

John I Jackson

David J Finger

D Grant Fash, Iii

John W Allison

Paul E Chandler

Laurence S McCabe

Arvind Jain

Bimba Rao

Shahrokh Shakouri

Kutay F Ustuner

James W Arenson

James E Chomas

Ting-Lan Ji

Rickard C Loftman

John Alexander Hossack

Bhaskar S Ramamurthy

Gregory L Holley

J Nelson Wright

Donald R Langdon

Seshadri Srinivasan

Janice L Marshall

Tommaso Mansi

Christopher R Cole

Ankur Kapoor

Linyong Pang

Helene C Houle

Jay Sterling Plugge

David P Duncan

Matthew I Haller

Brian M Normand

Leonard James Goodsell, Jr

Thilaka S Sumanaweera

Sriram Krishnan

Michael J Tierney

Stuart L Carp

Robert W Steins

John Douglas Marshall

Joan Carol Main

Wayne J Gueck

Xiaozheng Zeng

Ruth E Leibig

Gilles D Guenette

Carrie L Peressini

Shuwu Wu

Stanley S C Chim

Janna G Clark

Marc D Weinshenker

Dave Hedberg

Ken M Fowkes

Christopher S Hedgecock

Stanley S Chim

Les Oppenheimer

Cynthia Wolverton

Zafer Zamboglu

For quantification of blood flow by an ultrasound system, B-mode images generated with a multi-transmit, coherent image formation produce swirling or other speckle patterns in the blood regions. These patterns, as represented in specially formed B-mode images, are tracked over time to indicate two or three-dimensional velocity vectors of the blood at a B-mode resolution. Various visualizations may be provided at the same resolution, including the velocity flow field, flow direction, vorticity, vortex size, vortex shape, and/or divergence.

Quantification of blood flow with ultrasound B-mode imaging

For a classification-dependent user interface in ultrasound imaging with an ultrasound scanner, the ultrasound scanner classifies a view represented in an image. The user interface changes according to the view, allowing one or a few user inputs to be used for different user options or behavior combinations appropriate for the classified anatomy. The context from imaging alters the behavior of a given user input element of the user interface.

Image classification-dependent user interface in ultrasound imaging

By identifying locations of contrast agent response, an intensity-based metric of contrast agent signal is used to control a duration of microbubble destruction with a medical ultrasound scanner. Feedback from motion of the transducer may be used to indicate when a user perceives enough destruction. A combination of both an intensity-based metric and transducer motion may be used to control the duration of bursting.

Microbubble destruction for medical ultrasound imaging

Using computer-assisted classification and/or computer-assisted segmentation with or without monitoring the field of view for change, the workflow for ultrasound imaging may be made more efficient. The classification and/or segmentation is used to perform a next act in the sequence of acts making up the ultrasound examination. Rather than requiring a user to determine the act and implement the act, the ultrasound scanner determines and implements the act based on the identification and/or location of an imaged object. For example, the identification of the object as a kidney using a machine-learnt classifier triggers a color flow scan, and the location of the object determines a placement for the color flow region of interest (ROI), avoiding the user having to perform the ROI initiation and/or placement and increasing workflow efficiency.

Machine-aided workflow in ultrasound imaging

Motion artifacts are suppressed for three-dimensional parametric ultrasound imaging. Motion tracking is performed so that the parameter values derived over time are based on return from the same locations. Distortion due to the scan pattern is accounted for in the results of the motion tracking, such as by re-sampling the results to deal with discontinuity in time between data from adjacent sub-volumes and/or by aligning the scan pattern based on a direction of motion.

Motion artifact suppression for three-dimensional parametric ultrasound imaging

In multi-modality imaging fusion with ultrasound, one transducer is used for registering ultrasound scan data with scan data from another mode. This registration is used to then align scan data from a different ultrasound transducer with the scan data of the other mode. The alignment may account for differences in position sensing between the two transducers.

Registration for multi-modality medical imaging fusion with narrow field of view

In contrast agent imaging, a beamformer and transducer scan a region of a patient having contrast agents. A detector detects the contrast agents with at least two different contrast agent imaging techniques from ultrasound data resulting from the scanning. A processor compares responses of the contrast agents detected between the at least two different contrast agent imaging techniques and selects a relative contribution of the at least two different contrast agent imaging techniques. The selection is based on the comparing. Contrast agent imaging of the patient is performed using at least one of the contrast agent imaging techniques. The performance is based on the selected relative contribution.

Contrast agent sensitive medical ultrasound imaging

Compositions useful for target detection, imaging and treatment, as well as methods of production and use thereof, are disclosed herein.

Compositions useful for target, detection, imaging and treatment, and methods of production and use thereof

A Doppler gate is automatically positioned in spectral Doppler ultrasound imaging. Samples acquired for multiple PW Doppler gates are used for B-mode and/or F-mode detection over time without interleaving transmissions for the PW Doppler. The B-mode and/or F-mode information are used to track gate placement. Alternatively or additionally, characteristics spectra from different gate locations are used to select a gate location. Either tracking may be used to change the locations sampled and/or beam characteristics, such as centering the locations and beam focus on the selected gate location.

Automatic doppler gate positioning in spectral doppler ultrasound imaging

Steered spatial compounding is provided in ultrasound imaging. Component frames of data associated with different spatial response are processed to identify different sources of signals. Matched filtering and/or spatial variance with erosion distinguish between sources of signals, such as distinguishing between (1) anatomical structure and (2) soft tissue and/or noise. The locations in the patient are segmented by the source of signals and different compounding is applied for the different sources.

Component frame enhancement for spatial compounding in ultrasound imaging

Destruction for reperfusion in medical diagnostic ultrasound is synchronized to motion. Perfusion data for a volume is acquired sequentially for different segments of the volume. For a given segment, such as a planar region, motion tracking within the segment is performed. If sufficient registration or correlation exists at the completion of a sequence of scans for the current segment, then a lesser amount of movement is occurring. At this point, the transmission of contrast agent destructive acoustic energy is performed in the next segment. Tracking is repeated for the next segment to synchronize the switch to yet another segment. Other regions for tracking can be used. By controlling transmission of destruction pulses, more reliable perfusion quantities in a volume may be determined.

Motion synchronized destruction for three-dimensional reperfusion mapping in medical diagnostic ultrasound imaging

The effectiveness of contrast agent destruction is determined. Locations of ineffectively destroyed contrast agents are identified. The response from undestroyed contrast agents may be distinguished from response from tissue due to saturation or from rapid perfusion. The locations may be highlighted on resulting images, indicating to the user locations not associated with perfusion. The user may make a diagnosis on perfusion rather than a lack of destruction of contrast agents.

Contrast agent destruction effectiveness determination for medical diagnostic ultrasound imaging

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Redwood City, CA, United States of America

Ismayil M Guracar