Patent Description:
In contrast-enhanced imaging, a contrast agent is provided to an area or volume to be imaged in order to provide a higher signal strength from the area or volume, or selectively enhance signals from areas or volumes with high contrast concentration. For example, in contrast-enhanced ultrasound (CEUS), microbubbles may be injected into a subject's bloodstream and ultrasound images may be acquired of the subject's vasculature. Without the microbubbles, little to no signal may be provided by the blood vessels. In contrast accumulation imaging (CAI), multiple contrast-enhanced images (e.g., multiple image frames) are acquired and combined and/or normalized to form the final image, which can be used to map contrast agent progression and enhance vessel topology and conspicuity. Temporal accumulation imaging of CEUS has been commercialized and widely used for vascular visualization. However, CEUS has limited spatial resolution due to the large size of the point spread function (PSF) in contrast mode. The PSF is a measure of blurring or spreading of a point source by an imaging system. CEUS may also have strong residual clutter artifacts as well as vulnerability to patient induced motion due to the combining of multiple image frames to form the final image.

Super-resolution imaging (SRI) is a CEUS technique that makes it potentially possible for improved diagnosis of vascular diseases and cancer malignancy by providing morphological microvascular images as well as functional microcirculation maps in depth with detail not previously possible using conventional approaches. In a common SRI technique, each super-resolved image is obtained by two steps: (<NUM>) localizing the center of each separable microbubble in an image and then (<NUM>) accumulating these centers over thousands of images. The position of each microbubble is obtained by taking the local maxima of each microbubble intensity profile. This means that the center of each microbubble can be seen and represented as a single-pixel dot. The accumulation of the center positions of microbubbles is the probability density mapping of microbubbles, which is the super-resolved image of the microvasculature.

However, the timescale of acquisition is challenging when imaging a large region or a pathology where the bubble inflow dynamics are especially important (e.g. visualizing rapid wash-in). SRI typically requires tens or hundreds of thousands of individual contrast imaging frames, corresponding to a combination of very high imaging frame rates (often ><NUM>) and very long acquisition times (e.g., several minutes) compared to conventional contrast ultrasound scans.

<NPL> discloses super-resolution ultrasound enabling detailed assessment of the fine vascular network by pinpointing individual microbubbles using ultrasound contrast agents.

<NPL> discloses a two-stage motion estimation method, which is a combination of affine and nonrigid estimation, for super resolution ultrasound imaging.

<NPL> discloses ultrasound imaging at ultrafast frame rates.

<NPL> discloses microvascular imaging using imaging without contrast agents.

<NPL> discloses signal-based and sharpness-based axial localization for super-resolution ultrasound imaging.

Systems and methods for a multi-level resolution vascular imaging approach is disclosed. Systems and methods may include (<NUM>) one or more contrast imaging modes with conventional and enhanced spatial resolutions are employed to display large to small vessels of a vascular tree within a large ROI and (<NUM>) a SRI mode is created for delineation of both microvascular morphology and functional microcirculation within one or more small ROIs placed in selected locations within the large ROI. The advantages of the multi-level CEUS imaging according to principles of the present disclosure may include (<NUM>) adequate display of different levels of vascularity from large to small vessels to anatomically and functionally-detailed micro-vascular circulation; (<NUM>) shortened processing time for SRI reconstruction and consequently prompt display of the microstructure; and (<NUM>) allowing for effective correction of local physiological motion which may be crucial in SRI.

In accordance with at least one example disclosed herein, an ultrasound imaging system may include an ultrasound probe for transmitting and receiving ultrasound signals for a plurality of ultrasound images, wherein the plurality of ultrasound images are contrast enhanced ultrasound images, a display configured to display at least one of the plurality of ultrasound images, a user interface configured to receive a user input via at least one user control, wherein the user input indicates a first region of interest (ROI) within the at least one image of the plurality of ultrasound images, wherein the first ROI includes less than an entirety of the at least one of the plurality of ultrasound images, and at least one processor in communication with the user interface, the at least one processor configured to: process at least some of the plurality of ultrasound images with a first processing technique, and process in the first ROI at least some of the plurality of ultrasound images with a second processing technique, wherein the second processing technique has a higher spatial resolution and a lower temporal resolution than the first processing technique, wherein the display is further configured to display the at least some of the plurality of ultrasound images processed with the first processing technique and the at least some of the plurality of ultrasound images processed with the second processing technique.

In accordance with at least one example disclosed herein, a method may include receiving a plurality of ultrasound images, wherein the plurality of ultrasound images are contrast enhanced ultrasound images, displaying at least one of the plurality of ultrasound images, receiving an indication of a region of interest (ROI) within the at least one of the plurality of ultrasound images, wherein the ROI includes less than an entirety of the at least one of the plurality of ultrasound images, processing a first set of the plurality of ultrasound images with a first processing technique, and processing in the ROI a second set of the plurality of ultrasound images with a second processing technique, wherein the second processing technique has a higher spatial resolution and a lower temporal resolution than the first processing technique.

In accordance with at least one example disclosed herein, a non-transitory computer readable medium including instructions, that when executed, may cause an ultrasound imaging system to receive a plurality of ultrasound images, wherein the ultrasound images are contrast enhanced ultrasound images, display at least one of the plurality of ultrasound images, receive an indication of a region of interest (ROI) within the at least one of the plurality of ultrasound images, wherein the first ROI includes less than an entirety of the at least one of the plurality of ultrasound images, process a first set of the plurality of ultrasound images with a first processing technique, and process in the ROI a second set of the plurality of ultrasound images with a second processing technique, wherein the second processing technique has a higher spatial resolution and a lower temporal resolution than the first processing technique.

The following description of certain exemplary examples is merely exemplary in nature and is in no way intended to limit the disclosure or its applications or uses. In the following detailed description of examples of the present systems and methods, reference is made to the accompanying drawings which form a part hereof, and in which are shown by way of illustration specific examples in which the described systems and methods may be practiced. These examples are described in sufficient detail to enable those skilled in the art to practice the presently disclosed systems and methods, and it is to be understood that other examples may be utilized and that structural and logical changes may be made. Moreover, for the purpose of clarity, detailed descriptions of certain features will not be discussed when they would be apparent to those with skill in the art so as not to obscure the description of the present disclosure. The following detailed description is therefore not to be taken in a limiting sense, and the scope of the present systems and methods is defined only by the appended claims.

As one of the major complications of diabetes, chronic kidney disease leads to significant changes of renal microvasculature and perfusion in the early stage. While contrast enhanced ultrasound (CEUS) is sensitive to changes in microvascular perfusion, early changes in microstructures and microcirculations are hard to image with conventional ultrasound due to poor spatial resolution. This also applies for early detection of chronic peripheral vascular diseases as well as early diagnosis of malignant tumors.

CEUS has been employed clinically for imaging organ/tumor vascularity as well as assessing tissue perfusion. However, its inherently low spatial resolution prevents CEUS from adapting its spatial resolution properly for different clinical needs. Owing to the lack of vascular clarity in small vessels and capillaries in conventional CEUS, super-resolution imaging (SRI) has been developed in recent years to improve the spatial resolution of ultrasound imaging by localizing contrast microbubbles flowing in microvasculature. However, as discussed previously, SRI inherently has both little motion tolerance and low temporal resolution due to its two fundamental requirements of precise microbubble localization and long frame accumulation.

Although SRI can image very fine structures and provide functional information down to the capillary level, it may be impractical to construct and display a super-resolution image of a large region (such as a large portion of an entire organ, or a tumor). In addition, it may be ineffective to utilize SRI to image and display large vessels since already existing conventional high temporal resolution imaging modalities are adequate for large vessels. Consequently, a multi-level contrast imaging approach as disclosed herein may provide more effective and/or optimal views of various levels of a particular vasculature. A multimodal ultrasound vascular imaging system according to principles of the present disclosure may be capable of providing high temporal resolution for large vessel (e.g., CEUS) and high spatial resolution for microvascular imaging (e.g., SRI).

The present disclosure is directed to systems and methods for multi-level vascular imaging for construction and display of vasculature from large to small vessels and micro-vessels using a combination of varying resolution CEUS flow imaging modalities. While one or more resolution flow imaging modes may be employed for imaging large to small vessels of a vascular tree within a large region of interest (ROI), a SRI mode is constructed for delineation of the microvascular morphology and directional microcirculation within one or more small ROIs placed in selected locations within a larger ROI. Examples of flow imaging modes include, but are not limited to CEUS, color Doppler, color power angiography (CPA), microflow imaging (MFI), CEUS-MFI, microvascular imaging (MVI), and high definition MVI (HD-MVI). In general, different vascular levels can be imaged with different modes for large vessels to small vessels to capillaries.

<FIG> shows a block diagram of an ultrasound imaging system <NUM> constructed in accordance with the principles of the present disclosure. An ultrasound imaging system <NUM> according to the present disclosure may include a transducer array <NUM>, which may be included in an ultrasound probe <NUM>, for example an external probe or an internal probe such as an intravascular ultrasound (IVUS) catheter probe. In other examples, the transducer array <NUM> may be in the form of a flexible array configured to be conformally applied to a surface of subject to be imaged (e.g., patient). The transducer array <NUM> is configured to transmit ultrasound signals (e.g., beams, waves) and receive echoes (e.g., received ultrasound signals) responsive to the transmitted ultrasound signals. A variety of transducer arrays may be used, e.g., linear arrays, curved arrays, or phased arrays. The transducer array <NUM>, for example, can include a two dimensional array (as shown) of transducer elements capable of scanning in both elevation and azimuth dimensions for 2D and/or 3D imaging. As is generally known, the axial direction is the direction normal to the face of the array (in the case of a curved array the axial directions fan out), the azimuthal direction is defined generally by the longitudinal dimension of the array, and the elevation direction is transverse to the azimuthal direction.

In some examples, the transducer array <NUM> may be coupled to a microbeamformer <NUM>, which may be located in the ultrasound probe <NUM>, and which may control the transmission and reception of signals by the transducer elements in the array <NUM>. In some examples, the microbeamformer <NUM> may control the transmission and reception of signals by active elements in the array <NUM> (e.g., an active subset of elements of the array that define the active aperture at any given time).

In some examples, the microbeamformer <NUM> may be coupled, e.g., by a probe cable or wirelessly, to a transmit/receive (T/R) switch <NUM>, which switches between transmission and reception and protects the main beamformer <NUM> from high energy transmit signals. In some examples, for example in portable ultrasound systems, the T/R switch <NUM> and other elements in the system can be included in the ultrasound probe <NUM> rather than in the ultrasound system base, which may house the image processing electronics. An ultrasound system base typically includes software and hardware components including circuitry for signal processing and image data generation as well as executable instructions for providing a user interface.

The transmission of ultrasonic signals from the transducer array <NUM> under control of the microbeamformer <NUM> is directed by the transmit controller <NUM>, which may be coupled to the T/R switch <NUM> and a main beamformer <NUM>. The transmit controller <NUM> may control the direction in which beams are steered. Beams may be steered straight ahead from (orthogonal to) the transducer array <NUM>, or at different angles for a wider field of view. The transmit controller <NUM> may also be coupled to a user interface <NUM> and receive input from the user's operation of a user control. The user interface <NUM> may include one or more input devices such as a control panel <NUM>, which may include one or more mechanical controls (e.g., buttons, encoders, etc.), touch sensitive controls (e.g., a trackpad, a touchscreen, or the like), and/or other known input devices.

In some examples, the partially beamformed signals produced by the microbeamformer <NUM> may be coupled to a main beamformer <NUM> where partially beamformed signals from individual patches of transducer elements may be combined into a fully beamformed signal. In some examples, microbeamformer <NUM> is omitted, and the transducer array <NUM> is under the control of the beamformer <NUM> and beamformer <NUM> performs all beamforming of signals. In examples with and without the microbeamformer <NUM>, the beamformed signals of beamformer <NUM> are coupled to processing circuitry <NUM>, which may include one or more processors (e.g., a signal processor <NUM>, a B-mode processor <NUM>, a Doppler processor <NUM>, and one or more image generation and processing components <NUM>) configured to produce an ultrasound image from the beamformed signals (i.e., beamformed RF data).

The signal processor <NUM> may be configured to process the received beamformed RF data in various ways, such as bandpass filtering, decimation, I and Q component separation, and harmonic signal separation. The signal processor <NUM> may also perform additional signal enhancement such as speckle reduction, signal compounding, and electronic noise elimination. The processed signals (also referred to as I and Q components or IQ signals) may be coupled to additional downstream signal processing circuits for image generation. The IQ signals may be coupled to a plurality of signal paths within the system, each of which may be associated with a specific arrangement of signal processing components suitable for generating different types of image data (e.g., B-mode image data, Doppler image data). For example, the system may include a B-mode signal path <NUM> which couples the signals from the signal processor <NUM> to a B-mode processor <NUM> for producing B-mode image data.

The B-mode processor <NUM> can employ amplitude detection for the imaging of structures in the body. The B-mode processor <NUM> may generate signals for tissue images and/or contrast images. The signals produced by the B-mode processor <NUM> may be coupled to a scan converter <NUM> and/or a multiplanar reformatter <NUM>. The scan converter <NUM> may be configured to arrange the echo signals from the spatial relationship in which they were received to a desired image format. For instance, the scan converter <NUM> may arrange the echo signal into a two dimensional (2D) sector-shaped format, or a pyramidal or otherwise shaped three dimensional (3D) format. In another example of the present disclosure, the scan converter <NUM> may arrange the echo signals into side-by-side contrast enhanced and tissue images. As explained further below, in some examples, the image processor <NUM> performs microbubble identification, localization, and accumulation.

The multiplanar reformatter <NUM> can convert echoes which are received from points in a common plane in a volumetric region of the body into an ultrasonic image (e.g., a B-mode image) of that plane, for example as described in <CIT>). The scan converter <NUM> and multiplanar reformatter <NUM> may be implemented as one or more processors in some examples.

A volume renderer <NUM> may generate an image (also referred to as a projection, render, or rendering) of the 3D dataset as viewed from a given reference point, e.g., as described in <CIT>). The volume renderer <NUM> may be implemented as one or more processors in some examples. The volume renderer <NUM> may generate a render, such as a positive render or a negative render, by any known or future known technique such as surface rendering and maximum intensity rendering.

In some examples, the system may include a Doppler signal path <NUM> which couples the output from the signal processor <NUM> to a Doppler processor <NUM>. The Doppler processor <NUM> may be configured to estimate the Doppler shift and generate Doppler image data. The Doppler image data may include color data which is then overlaid with B-mode (i.e. grayscale) image data for display. The Doppler processor <NUM> may be configured to filter out unwanted signals (i.e., noise or clutter associated with non-moving tissue), for example using a wall filter. The Doppler processor <NUM> may be further configured to estimate velocity and power in accordance with known techniques. For example, the Doppler processor may include a Doppler estimator such as an auto-correlator, in which velocity (Doppler frequency) estimation is based on the argument of the lag-one autocorrelation function and Doppler power estimation is based on the magnitude of the lag-zero autocorrelation function. Motion can also be estimated by known phase-domain (for example, parametric frequency estimators such as MUSIC, ESPRIT, etc.) or time-domain (for example, cross-correlation) signal processing techniques. Other estimators related to the temporal or spatial distributions of velocity such as estimators of acceleration or temporal and/or spatial velocity derivatives can be used instead of or in addition to velocity estimators. In some examples, the velocity and power estimates may undergo further threshold detection to further reduce noise, as well as segmentation and post-processing such as filling and smoothing. The velocity and power estimates may then be mapped to a desired range of display colors in accordance with a color map. The color data, also referred to as Doppler image data, may then be coupled to the scan converter <NUM>, where the Doppler image data may be converted to the desired image format and overlaid on the B-mode image of the tissue structure to form a color Doppler or a power Doppler image. For example, Doppler image data may be overlaid on a B-mode image of the tissue structure.

Output (e.g., B-mode images, Doppler images) from the scan converter <NUM>, the multiplanar reformatter <NUM>, and/or the volume renderer <NUM> may be coupled to an image processor <NUM> for further enhancement, buffering and temporary storage before being displayed on an image display <NUM>.

In some examples, the image processor <NUM> may process the images using different image processing techniques. For example, the image processor <NUM> may collect multiple images (e.g., sequential images acquired at different time points) and combine them to generate contrast accumulation images (e.g., MVI). In some examples, the image processor <NUM> may also analyze individual images to locate one or more microbubbles within the image and find the centers of the microbubbles and generate one or more SRI images based on SRI image processing techniques. Other image processing techniques may also be used (e.g., color Doppler, CPA, CEUS-MFI). According to principles of the present disclosure, the image processor <NUM> may process different regions of the images received from the scan converter <NUM> using different image processing techniques. For example, one or more regions may be processed using contrast accumulation imaging techniques and one or more regions may be processed using SRI techniques.

The different processing techniques may provide images of the regions that have both different temporal and spatial resolutions. For example, a region processed by MVI techniques may have lower spatial resolution and higher spatial resolution than a region processed by SRI techniques. In some examples, higher spatial resolution may be a result, at least in part, of a greater number of image frames being combined to generate a final image of the region. In some examples, higher temporal resolution may be a result, at least in part, of a fewer number of image frames being combined and/or a faster acquisition rate by the ultrasound probe (e.g., number of frames per second).

In some examples, the one or more regions processed using different image processing techniques may at least partially overlap. In some examples, different sets of images may be processed by the image processor <NUM> to process the different regions with different processing techniques (e.g., every other image may be used for the first region and the other images may be used for the second region). In some examples, which regions of the images are processed by what techniques by the image processor <NUM> may be based, at least in part, by setting a region of interest and/or an imaging mode by a user via the user interface <NUM>, as described further below.

According to principles of the present disclosure, in some examples, an ultrafast imaging mode with a same pulse sequence may be employed during/after the contrast agent injection/infusion. In some examples, the pulse sequence may be based on control signals provided by the transmit controller <NUM>. In some examples, imaging frames and/or relevant RF and/or IQ-data may be streamed to a computer-readable medium (e.g., local memory <NUM>) continuously during the entire contrast imaging length. The data may be provided from the beamformer <NUM>, the signal processor <NUM>, B-mode processor <NUM>, Doppler processor <NUM>, and/or scan converter <NUM>. The user interface <NUM> may allow control of how an image or ROI of a first imaging mode (e.g., CEUS) is displayed along with one or more additional images or ROIs of different imaging modes (e.g., SRI). In other examples, if not all imaging frames and/or relevant RF/IQ-data can be saved continuously, the interleaving of two pulse sequences can be used with one for the overview mode and another for the super-resolution imaging. In some examples, if system constraints do not allow simultaneous interleave/acquisition of different imaging modes, then when SRI is selected as an imaging mode, the SRI mode may operate with a realization similar to PW Doppler where sparse updates to the reference image guide the clinician with plane selection while a long accumulation/streaming operation occupies the majority of the system process.

A graphics processor <NUM> may generate graphic overlays for display with the images. These graphic overlays can contain, e.g., standard identifying information such as patient name, date and time of the image, imaging parameters, and the like. For these purposes the graphics processor may be configured to receive input from the user interface <NUM>, such as a typed patient name or other annotations. The user interface <NUM> can also be coupled to the multiplanar reformatter <NUM> for selection and control of a display of multiple multiplanar reformatted (MPR) images.

The system <NUM> may include local memory <NUM>. Local memory <NUM> may be implemented as any suitable non-transitory computer readable medium (e.g., flash drive, disk drive). Local memory <NUM> may store data generated by the system <NUM> including B-mode images, masks, executable instructions, inputs provided by a user via the user interface <NUM>, or any other information necessary for the operation of the system <NUM>.

As mentioned previously system <NUM> includes user interface <NUM>. User interface <NUM> may include display <NUM> and control panel <NUM>. The display <NUM> may include a display device implemented using a variety of known display technologies, such as LCD, LED, OLED, or plasma display technology. In some examples, display <NUM> may comprise multiple displays. The control panel <NUM> may be configured to receive user inputs (e.g., exam type, selection of ROIs). The control panel <NUM> may include one or more hard controls (e.g., buttons, knobs, dials, encoders, mouse, trackball or others). In some examples, the control panel <NUM> may additionally or alternatively include soft controls (e.g., GUI control elements or simply, GUI controls) provided on a touch sensitive display. In some examples, display <NUM> may be a touch sensitive display that includes one or more soft controls of the control panel <NUM>.

According to principles of the present disclosure, in some examples, a user may set one or more ROIs via the user interface <NUM>. For example, the user may set a ROI on an image provided on display <NUM>. The ROI may be set by the user by placing a selection box on the image on the display <NUM> by using one or more controls on the control panel <NUM>. The user may determine an imaging mode for the portion of the image within the ROI by providing an input via the user interface <NUM>. In some examples, the user may select one or more ROIs and indicate different imaging modes for each ROI. In some examples, an ROI may be included within and/or overlap with another ROI. In some examples, a maximum size of the ROI may be based, at least in part, on the imaging mode selected by the user. For example, a maximum size of the ROI for accumulation CEUS imaging may be larger than a maximum size of the ROI for SRI. The selected imaging modes may affect the processing of the images by the image processor <NUM> and/or the acquisition settings (e.g., pulse sequences indicated by the transmit controller <NUM>) in addition to affecting the images displayed on display <NUM>.

In some examples, various components shown in <FIG> may be combined. For instance, image processor <NUM> and graphics processor <NUM> may be implemented as a single processor. In another example, the scan converter <NUM> and multiplanar reformatter <NUM> may be implemented as a single processor. In some examples, various components shown in <FIG> may be implemented as separate components. For example, signal processor <NUM> may be implemented as separate signal processors for each imaging mode (e.g., B-mode, Doppler). In some examples, one or more of the various processors shown in <FIG> may be implemented by general purpose processors and/or microprocessors configured to perform the specified tasks. In some examples, one or more of the various processors may be implemented as application specific circuits. In some examples, one or more of the various processors (e.g., image processor <NUM>) may be implemented with one or more graphical processing units (GPU).

<FIG> is a block diagram illustrating an example processor <NUM> according to principles of the present disclosure. Processor <NUM> may be used to implement one or more processors described herein, for example, image processor <NUM> shown in <FIG>. Processor <NUM> may be any suitable processor type including, but not limited to, a microprocessor, a microcontroller, a digital signal processor (DSP), a field programmable array (FPGA) where the FPGA has been programmed to form a processor, a graphical processing unit (GPU), an application specific circuit (ASIC) where the ASIC has been designed to form a processor, or a combination thereof.

The processor <NUM> may include one or more cores <NUM>. The core <NUM> may include one or more arithmetic logic units (ALU) <NUM>. In some examples, the core <NUM> may include a floating point logic unit (FPLU) <NUM> and/or a digital signal processing unit (DSPU) <NUM> in addition to or instead of the ALU <NUM>.

The processor <NUM> may include one or more registers <NUM> communicatively coupled to the core <NUM>. The registers <NUM> may be implemented using dedicated logic gate circuits (e.g., flip-flops) and/or any memory technology. In some examples the registers <NUM> may be implemented using static memory. The register may provide data, instructions and addresses to the core <NUM>.

In some examples, processor <NUM> may include one or more levels of cache memory <NUM> communicatively coupled to the core <NUM>. The cache memory <NUM> may provide computer-readable instructions to the core <NUM> for execution. The cache memory <NUM> may provide data for processing by the core <NUM>. In some examples, the computer-readable instructions may have been provided to the cache memory <NUM> by a local memory, for example, local memory attached to the external bus <NUM>. The cache memory <NUM> may be implemented with any suitable cache memory type, for example, metal-oxide semiconductor (MOS) memory such as static random access memory (SRAM), dynamic random access memory (DRAM), and/or any other suitable memory technology.

The registers <NUM> and the cache <NUM> may communicate with controller <NUM> and core <NUM> via internal connections 220A, 220B, 220C and 220D. Internal connections may implemented as a bus, multiplexor, crossbar switch, and/or any other suitable connection technology.

Inputs and outputs for the processor <NUM> may be provided via a bus <NUM>, which may include one or more conductive lines. The bus <NUM> may be communicatively coupled to one or more components of processor <NUM>, for example the controller <NUM>, cache <NUM>, and/or register <NUM>. The bus <NUM> may be coupled to one or more components of the system, such as display <NUM> and control panel <NUM> mentioned previously.

The bus <NUM> may be coupled to one or more external memories. The external memories may include Read Only Memory (ROM) <NUM>. ROM <NUM> may be a masked ROM, Electronically Programmable Read Only Memory (EPROM) or any other suitable technology. The external memory may include Random Access Memory (RAM) <NUM>. RAM <NUM> may be a static RAM, battery backed up static RAM, Dynamic RAM (DRAM) or any other suitable technology. The external memory may include Electrically Erasable Programmable Read Only Memory (EEPROM) <NUM>. The external memory may include Flash memory <NUM>. The external memory may include a magnetic storage device such as disc <NUM>. In some examples, the external memories may be included in a system, such as ultrasound imaging system <NUM> shown in <FIG>, for example local memory <NUM>.

<FIG> is an illustration of example images <NUM>, <NUM> for a dual-level resolution CEUS system according to principles of the present disclosure. The images <NUM>, <NUM> were acquired from a kidney <NUM>, an organ with a vascular tree. Image <NUM> illustrates a first imaging mode, which is a contrast-enhanced color Doppler imaging for large arteries and veins. Image <NUM> illustrates a second imaging mode, a SRI mode for micro structures <NUM> and directional microcirculation. In some embodiments, image <NUM> and/or image <NUM> may be provided as part of a sequence of images (e.g., a cineloop).

Image <NUM> provides an overview of substantially the entire organ with suspicious regions that may require additional investigation. A user may investigate these suspicious regions by selecting a ROI within image <NUM> via a user interface (user interface <NUM>). In the example shown in <FIG>, the ROI is selected by placing a rectangular box <NUM> within the image <NUM>. The rectangular box <NUM> may be moved around during an interactive investigation in some examples.

The image <NUM> is an example of a zoomed-in detailed vascular map with both structural and functional information on the capillary flow scale obtained via SRI. In some examples, processing ultrasound images to generate the SRI image may be performed by an image processor, such as image processor <NUM>.

In some examples, the images <NUM> and <NUM> may be generated without switching between different imaging modes, e.g., by interleaving acquisition of the ultrasound signals used to generate a respective one of the images <NUM> and <NUM>. In some examples, the interleaving of these visualizations may be closely related to the pulse sequence used for one or both of the images <NUM> and <NUM> and/or post-processing. In some examples, imaging pulse sequences may be mostly determined by the position of the large region for color Doppler imaging on the image <NUM> and post-processing and contrast recording time may be primarily regulated by spatial resolution levels on image <NUM>.

<FIG> is an illustration of example images <NUM>, <NUM>, <NUM>, <NUM> for a multi-level resolution CEUS system according to principles of the present disclosure. The images in <FIG> show a tumor <NUM> in a liver. Image <NUM> is a grayscale contrast imaging image with high temporal resolution but low spatial resolution which may be useful for observing wash-in contrast kinetics of the tumor <NUM>. Image <NUM> shows a high-definition accumulation imaging image within a ROI indicated by box <NUM>. The image within box <NUM> has an intermediate temporal resolution and intermediate spatial resolution which may provide better vascular definition of large to small arteries in the tumor. In some examples, the image in box <NUM> may be generated by HD-MVI. Example systems and methods that may be used to generate the HD-MVI image is described in <CIT>.

Image <NUM> shows a second ROI indicated by box <NUM> placed within box <NUM>. Image <NUM> is an image generated from the second ROI. Image <NUM> is a low temporal resolution, high spatial resolution SRI image which may allow viewing of micro structures and directional microcirculations. The lower temporal resolution may be due, at least in part, to a large number of frames that are combined to generate the SRI image. However, this large number of frames (e.g., <NUM>,<NUM> frames) may provide higher spatial resolution.

The terms "high," "low," and "intermediate" in reference to the resolutions of the images are used to describe resolutions of the images in reference to the resolutions of the other images shown in <FIG>. Thus, in some examples, an image with higher temporal resolution may combine fewer frames and/or have a higher acquisition rate than an image with intermediate or lower temporal resolution. Similarly, in some examples, an image with higher spatial resolution may combine more frames and/or have more densely spaced scan lines than images with intermediate or lower spatial resolution. Furthermore, while the ROI for image <NUM> is shown here as selected on the intermediate image <NUM>, in some examples, the ROI for the low temporal, high spatial resolution SRI image may be selected on the first image <NUM> and the intermediate image and associated steps may be omitted.

In some examples, image <NUM> may pop-up (e.g., pop-up window) within or adjacent to image <NUM>. In some examples the ROIs indicated by box <NUM> and/or box <NUM> may be moved around by a user during an investigation.

As mentioned previously, an SRI image is accumulation of the center positions of microbubbles and thus the probability density mapping of microbubbles. In some examples, a confidence score may be generated based on the probability density calculations for the center positions of the microbubbles. For example, the confidence score may be calculated based on a correlation map between two or more consecutive frames used to generate the SRI image. In some examples, the correlation value between two consecutive frames may be averaged across multiple correlation values calculated for consecutive pairs of frames used to generate the SRI image. The correlation may be normalized to a value between <NUM> and <NUM>. The normalized correlation value may be used as the confidence score. This confidence score indicates that a sufficient number of frames have been accumulated for generating the SRI image and/or motion during frame accumulation was sufficiently low. The score and/or a qualitative indication of the confidence score is provided to the user. In the example shown in <FIG>, a ring <NUM> surrounding image <NUM> provides a qualitative indication of the confidence score by displaying different colors which correspond with different confidence score ranges. For example, ring <NUM> may be a first color (e.g., red) if the confidence score is below a threshold value (e.g., <NUM>, <NUM>) and a second color (e.g., green) if the confidence score is equal to or exceeds the threshold value. Additional colors and threshold values may be used.

As shown in <FIG> and <FIG>, there are a number of ways to reconstruct and display the multi-level vascular images according to principles of the present disclosure. In some examples, a new level of the vascular imaging within a selected "large" ROI pops up and replaces the current level image once the ROI is selected. In another example, a new level of the vascular imaging within a selected "small" ROI pops up once the ROI is selected and the new window may be displayed next to the current level image. In some examples, the two preceding examples may be combined. As discussed previously, there may be a number of control and/or display components for the user interface (e.g., user interface <NUM>). A ROI may be selected with a pointer and/or mouse or drawn by a finger interactively on a touch image panel.

As illustrated in the example shown in <FIG>, there are three resolution levels: The first level resolution imaging is usually a real-time CEUS for overviewing and then determining the "large" ROI enclosure of the tumor and its feeding vessels. All contrast images frames may be collected and processed by an image processor (e.g., image processor <NUM>) once contract injection is indicated by the user via the user interface. The second level resolution imaging is an accumulation imaging mode with its resolution enhanced with microbubble localization and tracking techniques (e.g., HD-MVI). Once the "large" ROI window is selected, the HD-MVI image within the window will be updated continuously with images frames acquired before and after the ROI selection. The temporal interval for the imaging accumulation may be controlled by the user via the user interface in some examples. The third level resolution imaging is a super-resolution imaging (SRI) mode. Once the "small" ROI is selected, a SRI image within a pup-up window will be updated until sufficient image frames are collected (with images frames acquired before and after the ROI selection).

<FIG> is a flow chart <NUM> of a method according to principles of the present disclosure. In some examples, the method may be performed by the system <NUM> shown in <FIG>.

At block <NUM>, a step of "receiving a plurality of ultrasound images" is performed. In some examples, the ultrasound images may be received by an image processor, such as image processor <NUM>. At block <NUM>, a step of "displaying at least one of the plurality of ultrasound images" is performed. The ultrasound images may be displayed on a display, such as display <NUM> in some examples.

At block <NUM>, a step of "receiving an indication of a ROI" is performed. In some examples, the ROI may be indicated within the at least one of the plurality of ultrasound images. In some examples, the ROI includes less than an entirety of the at least one of the plurality of ultrasound images. In some examples, the indication may be a user input received via a user interface, such as user interface <NUM>. In some examples, a user may use a control panel <NUM> to provide the user input to indicate the ROI.

At block <NUM>, a step of "processing a first set of the plurality of ultrasound images with a first processing technique" is performed. At block <NUM>, a step of "processing in the ROI a second set of the plurality of ultrasound images with a second processing technique" is performed. In some examples, the processing may be performed by the image processor. The second processing technique has a higher spatial resolution and a lower temporal resolution than the first processing technique. In some examples, the first set and the second set include the same images. According to the invention, the first processing technique is a contrast enhanced ultrasound processing technique and the second processing technique is a super resolution imaging (SRI) processing technique. In other examples, the first processing technique may be a Doppler processing technique. In some examples, block <NUM> may be performed before block <NUM>. In some examples, blocks <NUM> and <NUM> may be performed simultaneously.

According to the invention, the method shown in FIG. further includes displaying the images processed by the first and/or second processing techniques, for example, on the display.

According to the invention, the method shown in <FIG> further includes calculating a confidence score when the second processing technique is an SRI processing technique. The confidence score is based, at least in part, on the SRI processing technique. In some examples, the confidence score may be displayed with the ultrasound images. In some examples, the confidence score may be provided qualitatively, for example, as a colored ring as discussed in reference to <FIG>.

In some examples, the method shown in <FIG> may further include acquiring ultrasound signals for generating the plurality of ultrasound images. The acquiring may be performed by an ultrasound transducer array, such as transducer array <NUM> included in ultrasound probe <NUM>. In some examples, the acquiring may be under the control of a transmit controller, such as transmit controller <NUM>. The control signals may indicate one or more pulse sequences in some examples. In some examples, acquisition of ultrasound signals for generating the first set of the plurality of ultrasound images are interleaved with acquisition of ultrasound signals for generating the second set of the plurality of ultrasound images. For example, the interleaving may be based on control signals provided by the transmit controller to the ultrasound probe. In some examples, the method shown in <FIG> may further continuously streaming data corresponding to the ultrasound signals to a computer readable medium, for example, local memory <NUM>.

Two non-limiting examples of interleaved acquisition are provided herein for illustration of the principles of the present disclosure. In a first example, the frame-to-frame interleaving is performed. In this form of interleaving, one or more frames of a first imaging type are acquired followed by acquisition of one or more frames of a second imaging type. In some applications, this may be followed by acquisition of one or more frames of a third imaging type. This acquisition sequence is then repeated for the duration of the scan, or at least as long as images of the different imaging modes are desired. For example, a B-mode frame, which may be displayed as either a "nonlinear" contrast image for microbubbles, or a "linear" anatomic image for tissue, or both, a color imaging frame (e.g., Doppler power or velocity map, or both), and/or a number of SRI frames can be selectively put together in one or more frame-to-frame sequences in any order. In some cases, the SRI image may be an accumulation of many ultra-fast imaging frames.

In a second interleaving example, all of the acquired frames are same (e.g., each frame for B-mode and/or color Doppler, SRI. That is, the acquisition parameters for generating the different images may be the same. For example, an ultra-fast imaging frame may include multiple beams and/or directions and/or a number of pulses that are transmitted and received along each beam or direction. In some examples, the pulses may be different (e.g., different frequency, duration, intensity). The received pulses from multiple frames may then be extracted and/or accumulated to form images for the different imaging modes (e.g., B-mode, color Doppler, and/or SRI images). For example, if transmit pulse waveforms for B-mode, color Doppler, and SRI are different, the pulses for B-mode, color Doppler, and SRI may be transmitted along the same beam or direction in sequence. In another example, if transmit pulse waveforms for B-mode or color Doppler are the same as a part of SRI waveforms, the pulses for SRI alone may be sufficient.

Optionally, in some examples, the method shown in <FIG> may further include receiving an indication of a second ROI, for example, via the user interface. The method may further include processing in the second ROI a third set of the plurality of ultrasound images with a third processing technique. Again, the processing may be performed by an image processor. In some examples, the third processing technique may have a higher spatial resolution and a lower temporal resolution than the first processing technique and a lower spatial resolution and higher temporal resolution than the second processing technique.

The advantages of the multi-level vascular imaging according to the principles of the present disclosure may include adequate display of spatially detailed micro-vasculature within small ROIs, shortened processing time for SRI reconstruction for prompt display of the microstructure, and allowing for effective correction of localized physiological motion which may be important in SRI.

In various examples where components, systems and/or methods are implemented using a programmable device, such as a computer-based system or programmable logic, it should be appreciated that the above-described systems and methods can be implemented using any of various known or later developed programming languages, such as "C", "C++", "FORTRAN", "Pascal", "VHDL" and the like. Accordingly, various storage media, such as magnetic computer disks, optical disks, electronic memories and the like, can be prepared that can contain information that can direct a device, such as a computer, to implement the above-described systems and/or methods. Once an appropriate device has access to the information and programs contained on the storage media, the storage media can provide the information and programs to the device, thus enabling the device to perform functions of the systems and/or methods described herein. For example, if a computer disk containing appropriate materials, such as a source file, an object file, an executable file or the like, were provided to a computer, the computer could receive the information, appropriately configure itself and perform the functions of the various systems and methods outlined in the diagrams and flowcharts above to implement the various functions. That is, the computer could receive various portions of information from the disk relating to different elements of the above-described systems and/or methods, implement the individual systems and/or methods and coordinate the functions of the individual systems and/or methods described above.

In view of this disclosure it is noted that the various methods and devices described herein can be implemented in hardware, software, and/or firmware. Further, the various methods and parameters are included by way of example only and not in any limiting sense. In view of this disclosure, those of ordinary skill in the art can implement the present teachings in determining their own techniques and needed equipment to affect these techniques, while remaining within the scope of the invention. The functionality of one or more of the processors described herein may be incorporated into a fewer number or a single processing unit (e.g., a CPU) and may be implemented using application specific integrated circuits (ASICs) or general purpose processing circuits which are programmed responsive to executable instructions to perform the functions described herein.

Of course, it is to be appreciated that any one of the examples, examples or processes described herein may be combined with one or more other examples, examples and/or processes or be separated and/or performed amongst separate devices or device portions in accordance with the present systems, devices and methods.

Claim 1:
An ultrasound imaging system (<NUM>) comprising:
a display (<NUM>) configured to display at least one of a plurality of ultrasound images generated by an ultrasound probe (<NUM>) for transmitting-receiving ultrasound signals, wherein the plurality of ultrasound images are contrast-enhanced ultrasound images;
a user interface (<NUM>) configured to receive a user input via at least one user control (<NUM>), wherein the user input indicates a first region of interest (ROI) within the at least one image of the plurality of ultrasound images, wherein the first ROI includes less than an entirety of the at least one of the plurality of ultrasound images; and
at least one processor (<NUM>) in communication with the user interface, the at least one processor configured to:
process at least some of the plurality of ultrasound images with a first processing technique, wherein the first processing technique is a contrast enhanced ultrasound processing technique;
process in the first ROI at least some of the plurality of ultrasound images with a second processing technique, wherein the second processing technique has a higher spatial resolution and a lower temporal resolution than the first processing technique, wherein the second processing technique is a super resolution imaging (SRI) processing technique; and
generate a confidence score based, at least in part, on the second processing technique, wherein the confidence score is an indication of at least one of: a sufficient number of frames having been accumulated for generating the SRI image; and a sufficiently low motion during frame accumulation,
wherein the display is further configured to display the at least some of the plurality of ultrasound images processed with the first processing technique and the at least some of the plurality of ultrasound images processed with the second processing technique, and
wherein the generated confidence score and/or a qualitative indication of the generated confidence score is provided to the user.