The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

Non-resonant acoustic meta-material, method of fabrication, and uses thereof are disclosed herein. A layer of a first material is formed on a first substrate. A layer of a second material is formed on the layer of the first material to produce a stacked layer of first and second materials. At least a portion of the stacked layer of first and second materials is exposed to a radiation. The exposed portion of the second material is removed from the stacked layer of first and second materials. A cavity is formed using the removed exposed portion of the second material. The cavity includes a membrane formed from at least a portion of the first material. Additionally, an ultrasound system includes an ultrasound transducer and the non-resonant acoustic metamaterial coupled to the ultrasound transducer.

Contrast targets for medical imaging are disclosed herein which include a granule of superabsorbent polymer (SAP) material. The granule of SAP material has absorbed and formed crosslinks with a hydrogen-containing liquid to form an expanded SAP particle with at least one predetermined medical imaging physical property.

A testing apparatus has a phantom and a scanning mechanism. The scanning mechanism moves an ultrasonic probe in a scanning direction (x direction) while maintaining a contact state of the ultrasonic probe with the phantom. The phantom includes a heart simulated element simulating a heart which is a tissue of interest, and a simulated element simulating a tissue which is present at a periphery of the heart. A form of the heart simulated element changes continuously in the scanning direction. A change of a form thereof represents a change with respect to time of the heart.

A multi-modality fatty tissue mimicking material for phantoms for use with thermoacoustic imaging, ultrasound imaging and magnetic resonance imaging, which includes: an aqueous mixture of a 3% to 18% thickening agent, a 1% to 30% protein powder, a 0.1% to 2% ionic salt, a 30% to 85% water, and a 0% to 60% oil by weight, wherein the oil percentage corresponds to the fat percentage in tissue, further wherein the ionic salt percentage corresponds to an imaginary part of complex permittivity in tissue, and further wherein the water, oil and protein powder percentages correspond to the real part of complex permittivity in tissue.

The quality of ping-based ultrasound imaging is dependent on the accuracy of information describing the precise acoustic position of transmitting and receiving transducer elements. Improving the quality of transducer element position data can substantially improve the quality of ping-based ultrasound images, particularly those obtained using a multiple aperture ultrasound imaging probe, i.e., a probe with a total aperture greater than any anticipated maximum coherent aperture width. Various systems and methods for calibrating element position data for a probe are described.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

An anatomical model includes a first container, a second container disposed within the first container, and a third container disposed within the second container. The second container and the third container simulate components of kidney anatomy, and the model includes ballistics gel to improve echogenicity during an ultrasound-guided training procedure using the model.

For ultrasound-based proxy estimation with an ultrasound scanner, one or more ultrasound measurements are converted to a biomarker of a different modality, such as providing a measurement of a standard biomarker from histology or a lab test assay. The conversion uses a user-selected model, allowing for selection of one of various models relating ultrasound measurements to the biomarker. The ultrasound scan sequence may be optimized to the one or more biomarkers and the user-selected model. This improvement in use of ultrasound measurements relative to standard biomarkers may more likely result in acceptance of the less costly and more easily obtained ultrasound measures in diagnosis.

A filter circuit for an imaging device including a probe configured to propagate an ultrasonic wave through an object includes a diode bridge configured to receive, from a transducer of the probe, a composite signal that includes a test signal and a reflected signal. The reflected signal corresponds to reflected waves sensed by the transducer in response to the ultrasonic wave propagated through the object. The diode bridge is further configured to block the test signal from the composite signal and pass the reflected signal. The filter circuit further includes an output node configured to output the reflected signal and a first node and a second node that connect the diode bridge to a bias voltage. The bias voltage causes a bias current to flow from the first node to the second node through the diode bridge.