An example of a system for providing patient care guidance to a caregiver based on ultrasound detection of blood flow includes a defibrillator including an electrode assembly and an output device, a portable computing device communicatively coupled to the defibrillator and including an output device, a Doppler shift waveform evaluation engine disposed at the defibrillator and/or the portable computing device, and a wearable ultrasound blood flow sensor configured to couple to a patient and the defibrillator and/or the portable computing device and to generate data signals representing a Doppler shift waveform. The engine is configured to receive the data signals representing the waveform, generate caregiver instructions according to a cardiac arrest protocol, analyze the waveform based on the received data signals, identify heart-induced blood flow based on the waveform analysis, and generate and provide caregiver instructions according to a non-cardiac arrest protocol based on the identified heart-induced blood flow.

According to various embodiments, there is provided a probe structure. The probe structure includes a probe configured to emit acoustic energy. The probe structure further includes a load cell underneath and aligned with the probe. The probe structure further includes a probe hub including a cavity for receiving the probe and the load cell.

A method for forming a virtual 3D mathematical model of a dental system, including receiving DICOM files representing the dental system; identifying number and location of voxels of tissues of the dental system; combining the voxels of the tissues into voxels of organs of the dental system; combining the organs into the virtual 3D mathematical model of the dental system, wherein the virtual 3D mathematical models supports linear, non-linear and volumetric measurements of the dental system; and presenting the virtual 3D mathematical model to a user. The DICOM files can be cone beam or multispiral computed tomography, MRT, PET and/or ultrasonography. The tissues include enamel, dentin, pulp, cartilage, periodontium, and/or jaw bone. The organs include teeth, gums, temporomandibular joint and/or jaw. A size of the voxels is typically between 40 μm and 200 μm.

An ultrasound diagnostic apparatus 1 includes: a data acquisition unit 3 that repeatedly transmits an ultrasound beam to a subject a plurality of times in a range over a plurality of scanning lines to acquire a time-series data string of reflected waves from the subject; an analysis target data selection unit 7 that estimates the amount of relative positional deviation of a scatterer of the subject which is included in the time-series data string and excludes time-series data satisfying an exclusion condition based on the amount of positional deviation of the scatterer from the time-series data string to select analysis target data; an MTI filter unit 8 that removes a clutter component from the analysis target data; and a blood flow information estimation unit 9 that analyzes the analysis target data from which the clutter component has been removed to estimate blood flow information of the subject.

The present disclosure relates to noninvasive methods for detecting liver fibrosis. Disclosed herein are noninvasive liver fibrosis detection methods that use Doppler Ultrasound devices and a physics-based machine learning method. Further disclosed herein are methods for detecting liver fibrosis in a subject by detecting and measuring the presence of a shift in the frequency of blood flow in the hepatic vein as compared to the frequency of blood flow in the portal vein.

Provided is an ultrasound diagnosis apparatus including an image processor configured to generates an ultrasound image on the basis of an ultrasound signal, an image outputter configured to display the ultrasound image generated by the image processor on the basis of a plurality of parameters, a sound outputter configured to output Doppler sound of the ultrasound image, and a controller configured to control a volume of the Doppler sound on the basis of at least one of the plurality of parameters.

The present disclosure provides systems and methods for predicting a disease state of a subject using ultrasound imaging and ancillary information to the ultrasound imaging. At least two quantitative measurements of a subject, including at least one measurement taken using ultrasound imaging, as part of quantified information can be identified. One of the quantitative measurements can be compared to a first predetermined standard, included as part of ancillary information to the quantified information, in order to identify a first initial value. Further, another of the quantitative measurements can be compared to a second predetermined standard, included as part of the ancillary information, in order to identify a second initial value. Subsequently, the quantitative information can be correlated with the ancillary information using the first initial value and the second initial value to determine a final value that is predictive of a disease state of the subject.

Intravascular ultrasound (IVUS) imaging devices, systems, and method are provided. In one embodiment, an IVUS imaging device includes a flexible elongate member configured to be positioned within a lumen of a patient, the flexible elongate member comprising a proximal portion and a distal portion; and an imaging assembly disposed at the distal portion of the flexible elongate member. The imaging assembly includes a first ultrasound transducer operating at a first center frequency; and a second ultrasound transducer operating at a second center frequency different from the first center frequency.

An apparatus comprising an array of polymer-based capacitive micromachined ultrasonic transducers positioned on a substrate. The substrate may be at least substantially transparent to ionizing radiation, be flexible, and/or have walls positioned thereon to protect the transducers.

Systems and methods disclosed herein relate to the detection of irregular particles in a blood flow based on a determined relative speed of a particle suspended in a blood flow and/or other properties of a particle suspended in a blood flow including a particle's relative position within a blood vessel and a particles tendency to cluster with other particles suspended in a blood flow. Based on a determined relative speed and/or other relevant factors, the properties of irregular particles may also be measured, including the size, shape, and frequency of irregular particles in a blood flow. Machine learning techniques may be employed to determine patterns for the behavior of irregular particles suspended in a blood flow. These patterns may correspond to particular health risks and conditions.