Patent Description:
Non-alcoholic Fatty Liver Disease (NAFLD) has become one of the major causes of liver disease due to high prevalence of obesity and diabetes. Its incidence rate has been steadily increasing affecting about <NUM>%-<NUM>% population in western and developing countries. The clinical term for fatty liver is hepatic steatosis, defined as excessive accumulation of fat (above <NUM>%-<NUM>% by weight) in liver cells as triglycerides. Early stage of liver steatosis is silent and reversible by simple life style change, for instance through regular exercise and healthy dieting. Liver steatosis can turn into more advanced liver disease such as non-alcoholic steatohepatitis (NASH) and liver fibrosis. If left untreated at these stages, fatty liver will progress to end-stage disease including cirrhosis and primary cancer hepatocellular carcinoma.

In current clinical practice, the gold standard of fatty liver diagnosis is liver biopsy, an invasive procedure subject to sampling error and interpretation variability. Magnetic resonance proton density fat fraction (MR-PDFF) is considered the new reference standard for NAFLD diagnosis as it can provide a quantitative biomarker of liver fat content. However MR-PDFF is an expensive diagnostic tool which may not always be available, particularly at small hospitals. Compared to magnetic resonance imaging (MRI), ultrasound is a widely available and cost-effective imaging modality. Thus, ultrasound may be more suitable for screening and/or diagnosis of the general population with low risk.

Hepato-renal index (HRI), an ultrasound based method, has been used clinically for fatty liver detection. Excessive fat infiltration in liver increases acoustic backscattering coefficient leading to higher grayscale values in ultrasound B-mode imaging. At a normal state, liver parenchyma and renal cortex (RC) of the kidney have similar echogenicity. With more fat deposit, liver will appear more hyperechoic (i.e. brighter) than the RC. HRI is often calculated as the echo-intensity ratio of liver to RC. Based on the B-mode data echo intensities from the liver and kidney are estimated by selecting regions of interest (ROIs) within the liver parenchyma and the RC at a similar depth and then averaging grayscale echo-intensity values in the ROIs. However, there are reliability issues with HRI that limit its application, some due to user errors. For example, users may not acquire an image from an image plane that includes sufficient tissue in both the liver and the kidney or may select an ROI in the kidney that is at a different depth than the ROI in the liver. Accordingly, improved techniques for acquiring the HRI that are less prone to user errors are desired.

Reference is made to the following paper: <NPL>. This document describes an automated method for HRI calculation using a deep learning convolutional neural network.

Systems, apparatuses, and methods for guiding a user to acquire an image at a suitable image plane and to select ROIs in a liver and a kidney at a same depth are disclosed. In some examples, the image and/or selected ROIs may be analyzed to confirm sufficient quality for calculating HRI. If the selected ROIs are not of sufficient quality, the user may be prompted to select new ROIs and/or acquire a new image. In accordance with at least one example disclosed herein, an ultrasound imaging system may be configured to provide user guidance for acquiring images suitable for hepato-renal index measurements and may include a non-transitory computer readable medium encoded with instructions, and at least one processor in communication with the non-transitory computer readable medium and configured to execute the instructions, wherein when executed, the instructions cause the at least one processor to segment a liver region, a kidney region, and a hepatorenal interface from an image, fit a curve to the hepatorenal interface, calculate an anchor point at a midpoint of the curve, determine a tangent line to the curve at the anchor point, determine a horizontal line at the midpoint, calculate an angle between the tangent line and the horizontal line, and generate a visual cue for display, wherein the visual cue is based, at least in part, on the tangent line and the angle between the tangent line and the horizontal line, The imaging system may include a display configured to display the image and the visual cue as a graphical overlay over the image.

In accordance with at least one example disclosed herein, a method for providing user guidance for acquiring images suitable for hepato-renal index measurements may include receiving an image, segmenting a liver region, a kidney region, and a hepatorenal interface from the image, fitting a curve to the hepatorenal interface, calculating an anchor point at a midpoint of the curve, determining a tangent line to the curve at the anchor point, determining a horizontal line at the midpoint, calculating an angle between the tangent line and the horizontal line, displaying the image, and displaying a visual cue as a graphical overlay over the image, wherein the visual cue is based, at least in part the tangent line and the angle between the tangent line and the horizontal line.

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 without departing from the scope of the present disclosure. 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.

The hepato-renal index (HRI) is typically acquired based on the pixel intensities of the B-mode image displayed on an ultrasound imaging system. HRI can be a useful diagnostic indicator for fatty liver disease when it is measured properly. The reliability of HRI may suffer from poor image acquisition and/or improper selection of regions of interest (ROIs) on the liver and/or kidney.

During a liver imaging exam where an HRI measurement is desired, the liver and kidney should be imaged at an imaging plane that provides an adequate portion of the liver on one side of the image (typically on the left side of the image on current systems) and an adequate portion of the kidney on the other side of the image (typically on the right side of the image on current systems) for selection of ROIs in each organ. Furthermore, the image plane should be such that there is an adequate portion of both liver and kidney at similar imaging depths (preferably the same imaging depth). That is, the liver and kidney should appear roughly side-by-side rather than appearing stacked vertically in relation to the imaging beam. However, practically, there is a limited view of the liver and kidney due to the ribs. Typically, two-dimensional (2D) ultrasound images are obtained at particular scanning angles at particular anatomical locations. For example, an image of the hepatorenal interface at the 'Morrison' pouch may be obtained. Once the hepatorenal interface image is obtained, the probe may be rotated slightly to obtain the desired image of the liver and kidney approximately side-by-side for HRI measurement.

If the interface between the liver and kidney (the hepatorenal interface) is horizontal or near horizontal in the image (e.g., perpendicular or near perpendicular to the direction of the beam), the effective depth information of the kidney in the ultrasound image may be lacking, and may not be a reliable reference for HRI computation. A higher angle with respect to a horizontal line (e.g., a line perpendicular to the direction of the beam) at the interface between the liver and kidney may provide better effective depth information for the kidney. However, due to the ribs and other anatomy limiting the field of view of the ultrasound probe, in practice, the angle at the interface of the liver and kidney may be limited in range, for example, zero degrees to a few tens of degrees (e.g., <NUM> degrees, <NUM> degrees) during examination.

Given the anatomical realities imposing physical limits on ultrasound probe placement and orientation, acquiring a suitable image for HRI computations may require a significant amount of time and/or a skilled sonographer. Furthermore, once an image is acquired, determining appropriate ROIs in the image to use for the HRI may also require significant time and skill. Accordingly, techniques for assisting ultrasound users to acquire suitable images and appropriate ROIs is desirable.

The present disclosure is directed to systems and methods for guiding a user to select an acceptable imaging plane by providing visual cues as graphical overlays on an image on a display of an ultrasound imaging system during scanning. For example, the visual cue may include an indication of an angle of a line tangent to the hepatorenal interface. Once an image is acquired, statistical properties of an acquired image at different depth bands may be evaluated to confirm the acquired image is suitable for computing HRI measurements. In some examples, a graphical indication of the depth bands may be provided on the display to assist the user in selecting two ROIs at a same depth in the liver and kidney. In some applications, the reliability and reproducibility of HRI measurements may be improved. In some applications, the workflow for acquiring HRI measurements may be improved. In some applications, the time and/or skill required for the user to obtain HRI measurements may be reduced.

<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. The transducer array <NUM> is configured to transmit ultrasound signals (e.g., beams, waves) and receive echoes responsive to the 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 embodiments, 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 embodiments, 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 embodiments, 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 embodiments, 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 (e.g., processing circuitry <NUM> and user interface <NUM>).

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 embodiments, 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 embodiments, microbeamformer <NUM> is omitted, and the transducer array <NUM> is under the control of the main beamformer <NUM> which performs all beamforming of signals. In embodiments with and without the microbeamformer <NUM>, the beamformed signals of the main 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 (e.g., 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 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 can employ amplitude detection for the imaging of structures in the body. 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. 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 embodiments.

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 embodiments. 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 embodiments, 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, spectral Doppler) 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. The velocity and/or 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.

Outputs 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>. 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 <NUM> 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 ultrasound images, executable instructions, patient medical history, or any other information necessary for the operation of the system <NUM>. In some examples, local memory <NUM> may include multiple memories, which may be the same or of different type. For example, local memory <NUM> may include a dynamic random access memory (DRAM) and a flash memory.

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 embodiments, display <NUM> may comprise multiple displays. The control panel <NUM> may be configured to receive user inputs (e.g., exam type, store an image frame, freeze a window, ROI selection). The control panel <NUM> may include one or more hard controls (e.g., buttons, knobs, dials, encoders, mouse, trackball or others). In some embodiments, 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 embodiments, display <NUM> may be a touch sensitive display that includes one or more soft controls of the control panel <NUM>.

The components of system <NUM> shown in <FIG> may not comprise all of the components of system <NUM>. For example, system <NUM> may include one or more processors for implementing an operating system for the system, which may provide the GUI elements described herein. In another example, system <NUM> may include various interfaces for receiving or transmitting information wirelessly or via wired connections, such as transmitting acquired images to a picture archiving and communication system (PACS) and receiving electronic medical records from a hospital server.

In some embodiments, various components shown in <FIG> may be combined. For instance, the multiplanar reformatter <NUM> and volume renderer <NUM> may be implemented as a single processor. In some embodiments, 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 another example, the image processor <NUM> may be implemented as separate processors for different tasks and/or parallel processing of a same task. In some embodiments, 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, the processors may be configured by providing instructions for the tasks from a non-transitory computer readable medium (e.g., from local memory <NUM>). The instructions may then be executed by the processors. In some embodiments, one or more of the various processors may be implemented as application specific circuits. In some embodiments, one or more of the various processors (e.g., image processor <NUM>) may be implemented with one or more graphical processing units (GPU).

In some examples, a user may provide a user input via the user interface <NUM> when HRI measurements are desired from a subject. For example, the user may select an HRI option from a menu of an operating system of the system <NUM>. Optionally, the system <NUM> may import the subject's medical records (e.g., from the hospital information system (HIS)) and confirm the subject does not have chronic renal disease or coexisting chronic renal and liver disease that may make the subject unsuitable for HRI measurements. Alternatively, the system <NUM> may prompt the user to check the subject's medical records to confirm the subject is suitable for HRI measurements. If the subject is not suitable for HRI measurements, the subject may be referred to a different technique for assessing NAFLD. Other techniques may include different ultrasound techniques (e.g., machine learning-based analysis) and/or other imaging modalities (e.g., MRI).

The imaging system <NUM> may provide guidance to the user to acquire an appropriate imaging plane for obtaining HRI measurements. The user may acquire an initial image of the liver and kidney (or portions thereof). The imaging system <NUM> may determine a location of the hepatorenal interface (e.g., the interface) from the initial image, and based, at least in part, on the curve of the hepatorenal interface, the system <NUM> may provide guidance to the user for obtaining a suitable imaging plane for acquiring HRI measurements. In some examples, the location may be determined by one or more processors, such as image processor <NUM> of system <NUM>. The guidance may include one or more visual cues that indicate geometries of anatomical features and/or positions of anatomical features relative to one another, the image frame (e.g., field of view of the ultrasound probe <NUM>), and/or ultrasound beam (e.g., beam provided by transducer array <NUM>). The visual cues may allow a user to visually determine when suitable portions of the liver and kidney are present in the image and/or when the liver and kidney are at suitable positions relative to one another in the image. Examples of visual cues include, but are not limited to, an anchor point indicating a midpoint of the hepatorenal interface, a line tangent to the hepatorenal interface at the midpoint, a horizontal line through the midpoint, and/or a bounding box around a central portion of the image. In some examples, the visual cues may be provided as graphical overlays over the image. In some examples, the graphical overlay may be generated by one or more processors, such as image processor <NUM> and/or graphics processor <NUM>.

<FIG> shows an example image including a portion of a liver and a kidney according to principles of the present disclosure. Image <NUM> is an ultrasound image including a portion of a liver <NUM> and a portion of a kidney <NUM>. In some examples, the imaging system <NUM> may determine a location of the interface <NUM> between the liver <NUM> and kidney <NUM> automatically based on image segmentation techniques (e.g., edge detection, machine learning). Alternatively, the location of the interface <NUM> may be found by semi-automatic techniques. For example, the user may provide inputs via the user interface <NUM> to indicate one or more seed points <NUM> along the interface <NUM>. In some examples, such as the one shown in <FIG>, the user may provide <NUM>-<NUM> seed points <NUM>. The imaging system <NUM> may determine the location of the interface <NUM> based, at least in part, on the seed points <NUM> using image segmentation and/or deep learning techniques. In some examples, in addition to determining a location of the interface <NUM>, the imaging system <NUM> may segment the liver <NUM> and/or kidney <NUM> from the image <NUM>. In some examples, one or more processors of the imaging system <NUM>, such as image processor <NUM>, may determine the location of the interface <NUM> and/or segment the liver <NUM> and kidney <NUM> from the image.

In some examples, a curve may be fitted to the interface by the one or more processors. <FIG> shows an example image including a portion of a liver and a kidney with a curve fitted to the interface according to principles of the present disclosure. Image <NUM> is an ultrasound image including a portion of a liver <NUM> and a portion of a kidney <NUM>. At least a portion of the hepatorenal interface <NUM> is also visible in image <NUM>. A processor, such as image processor <NUM> may calculate an equation that defines a curve <NUM> fitted to the interface <NUM>. The curve <NUM> may be based at least in part, on automatic or semi-automatic segmentation techniques, for example, as described with reference to <FIG>, used to determine the location of the interface <NUM>. In some examples, nonlinear curve fitting techniques may be used to define the curve <NUM>. While the curve <NUM> may be provided on display <NUM> as an overlay on the image <NUM>, in other examples, the equation defining curve <NUM> may be calculated and stored in system <NUM>, but curve <NUM> need not be displayed.

Based, at least in part, on the curve of the hepatorenal interface, the system <NUM> may provide guidance to the user for obtaining a suitable imaging plane for acquiring HRI measurements. For example, the system <NUM> may provide one or more visual cues on display <NUM>. The visual cues may include one or more graphical overlays generated based, at least in part, on the curve of the hepatorenal interface.

<FIG> show example images on a display with graphical overlays to provide guidance to a user according to principles of the present disclosure. Display <NUM> may be included in display <NUM> in some examples. The display may provide an ultrasound image, such as image <NUM> in <FIG> and image <NUM> in <FIG>. Both image <NUM> and <NUM> include a portion of a liver <NUM>, a kidney <NUM>, and a hepatorenal interface <NUM>, which is the lighter grayscale region (e.g., the generally whiter line) between the liver <NUM> and kidney <NUM>. The display <NUM> may further provide visual cues as graphical overlays based, in part, on the geometry of the interface <NUM> for guiding the user to acquire an image suitable for obtaining HRI measurements. In some examples, the graphical overlays may include an anchor point <NUM>, a horizontal line <NUM>, a tangent line <NUM>, bounding box <NUM>, and/or angle indicator <NUM>. Although not shown in <FIG>, in some examples, the graphical overlays may further include a curve fitted to the hepatorenal interface <NUM>, such as curve <NUM> shown in <FIG>.

The images <NUM> and <NUM> may be segmented and a curve fitted to the hepatorenal interface <NUM> (even if the curve is not displayed) as described with reference to <FIG> and <FIG>. A midpoint of the curve fitted to the hepatorenal interface <NUM> may be calculated and indicated by anchor point <NUM>. A horizontal line (e.g., a line perpendicular to a center scan line of an ultrasound beam emitted by a transducer array, such as transducer array <NUM>) extending through the anchor point <NUM> may be calculated and provided as horizontal line <NUM>. However, in some examples, horizontal line <NUM> may not be shown on the display. A line tangent to the curve fitted to the hepatorenal interface <NUM> at the anchor point <NUM> may be calculated and provided as tangent line <NUM>. Optionally, in some examples, only the tangent line <NUM> is displayed, and the anchor point <NUM> is not provided on the display. The segmentation, curve, anchor point <NUM>, horizontal line <NUM>, and/or tangent line <NUM> may be calculated by one or more processors, such as image processor <NUM>. In some example, display information based on the calculations may be generated by another processor, such as graphics processor <NUM>.

The angle between the tangent line <NUM> and horizontal line <NUM> (even if not displayed) may be calculated by the one or more processors. A larger angle between the tangent line <NUM> and horizontal line <NUM> (e.g., a greater slope of the tangent line <NUM>) may provide a more suitable image for HRI measurements in some applications as it may permit more liver <NUM> and kidney <NUM> tissue to be present at a same depth. As shown in <FIG>, the angle <NUM> between the tangent line <NUM> and horizontal line <NUM> in image <NUM> is larger than angle <NUM> in image <NUM> in <FIG>. In image <NUM>, significant portions of the liver <NUM> and kidney <NUM> appear next to each other whereas in image <NUM>, the liver <NUM> is predominantly above the kidney <NUM>. Thus, in image <NUM>, there are little to no areas where there is liver <NUM> and kidney <NUM> tissue at a same depth for calculating HRI measurements.

By providing visual cue(s) of the angle between the tangent line <NUM> and the horizontal line <NUM> (and/or the slope of the tangent line <NUM>), a user can more easily, with visual guidance, find an appropriate image for HRI measurements. In some examples, display <NUM> may display at least the tangent line <NUM>, and in some cases also the anchor point <NUM> and/or the horizontal line <NUM>, and the user may "eyeball" (or visually estimate) when a suitable angle has been achieved, e.g., by visual inspection of the incline of the tangent line relative to horizontal. In some examples, a suitable angle may be thirty degrees or greater. In some examples, the numerical value of the angle and/or slope of the tangent line <NUM> may be provided as text on display <NUM> by angle indicator <NUM>. Additionally or alternatively, a qualitative indicator of the angle and/or slope may be provided by indicator <NUM>. In the example shown in <FIG>, text such as "Good" and "Too small" are provided. However, other qualitative indicators may be used such as different colors, different shapes, etc. The qualitative indicator may be based one or more thresholds. For example, the indicator may be "too small" or red when the angle is below thirty degrees and "good" or green when the angle is above thirty degrees. In some examples, the angle indicator <NUM> may be "built in" to one of the other graphic overlays. For example, tangent line <NUM> may change from one color to another color when a suitable angle is obtained. Visual cue(s) to guide the user may be provided in various other ways, for example by changing the color of the tangent line (e.g., from red or orange to green) when the angle between the tangent line and the horizontal is equal to or greater than the minimum threshold angle.

In addition to the suitable angle, in some examples, the user may be guided to maintain the midpoint of the hepatorenal interface <NUM>, as may be indicated by the anchor point <NUM>, near the center of the image <NUM>, <NUM>. This may help ensure that enough of the liver <NUM> and kidney <NUM> are visible for acquiring HRI measurements. In the example shown in <FIG>, the bounding box <NUM> is displayed to guide the user for proper placement of the anchor point <NUM> in the image. The location of the bounding box <NUM> may be determined based on a midpoint of the image <NUM>, <NUM>. The width of the bounding box <NUM> may be based, at least in part, by a width of the image <NUM>, <NUM>. For example, the bounding box <NUM> may be sized to include approximately <NUM>-<NUM>% of the scan lines/columns of pixels of the image <NUM>, <NUM>. In some examples, the bounding box <NUM> and/or anchor point <NUM> may change from one color to another when the anchor point <NUM> falls outside the bounding box <NUM>. In some examples, the display <NUM> may provide a text warning that the anchor point <NUM> is outside the bounding box <NUM>. Optionally, in examples where the anchor point <NUM> and/or bounding box <NUM> is not provided on the display, the tangent line <NUM> may change color and/or texture (e.g., solid to dashed line) when the midpoint of the hepatorenal interface <NUM> falls outside the central region of the image <NUM>, <NUM> defined by the bounding box <NUM> (even if not displayed).

Once the midpoint of the hepatorenal interface <NUM> is in a suitable location (e.g., anchor point <NUM> is within the bounding box <NUM>) and at a suitable angle (e.g., angle of <NUM> degrees or greater between the tangent line <NUM> and horizontal line <NUM>), the imaging plane may be suitable for acquiring an image for HRI measurements. The user may save the image (e.g., image <NUM>), for example, to local memory <NUM>.

Although <FIG> show anchor point <NUM>, a horizontal line <NUM>, a tangent line <NUM>, bounding box <NUM>, and angle indicator <NUM> displayed, in other examples, only some of the graphical overlays may be provided. As noted, in some examples, only the tangent line <NUM> may be provided. In some examples, only the angle indicator <NUM> may be provided. In some examples, only the tangent line <NUM> and angle indicator <NUM> may be provided. Other combinations of the visual cues may also be used. In some examples, a user may select which visual cues are provided, for example, by providing inputs via the user interface <NUM>.

Optionally, in some embodiments, the average intensity of pixels of the hepatorenal interface <NUM> may be calculated by the one or more processors. If the average intensity is too high, it may indicate that the echo intensity of the kidney <NUM>, particularly the RC of the kidney <NUM> may be too low for acquiring HRI measurements. In some examples, the width of the hepatorenal interface <NUM> may be approximately <NUM>-<NUM> pixels. The average intensity of a portion of the liver <NUM> may also be calculated. For example, a portion of the liver <NUM> (e.g., <NUM>-<NUM> pixels in width) at a same or similar depth as a portion of the hepatorenal interface <NUM>. In some examples, multiple portions of the liver <NUM> at same or similar depths at multiple portions of the hepatorenal interface <NUM>. The average intensity of the hepatorenal interface <NUM> (or one or more portions thereof) may be compared to the average intensity of the portion of the liver <NUM> (or multiple portions thereof) to determine if the imaging plane is suitable. In some examples, if the average intensity of the hepatorenal interface <NUM> is below a certain percentage of the average intensity of the liver <NUM> and/or above a certain percentage of the average intensity of the liver <NUM>, the imaging plane may not be suitable. For example, when the average intensity of the hepatorenal interface <NUM> is equal to or greater than <NUM>*average intensity of the liver <NUM>, but equal to or less than <NUM>*average intensity of the liver <NUM>, the imaging plane may be suitable.

Additionally or alternatively, the average intensity of the hepatorenal interface <NUM> may be compared to the maximum brightness of the image <NUM>, <NUM> to determine if the imaging plane is suitable. For example, if the average intensity of the hepatorenal interface <NUM> is greater than a certain percentage of the maximum brightness (e.g., <NUM>, <NUM>), then the hepatorenal interface <NUM> may be too bright and the kidney <NUM> may be too dark. In some examples, the average intensity of the hepatorenal interface <NUM> may be compared to both the maximum brightness of the image and the average intensity of the liver <NUM> to determine the suitability of the image plane.

In some examples, the display <NUM> may provide an indicator as to whether the average intensity of the pixels of the hepatorenal interface <NUM> is suitable as text in a similar manner to the angle indicator <NUM>. In some examples where the graphical overlay includes the curve fitted to the hepatorenal interface <NUM>, the curve may change color when the average intensity is within a suitable range.

Once an image is acquired, in some examples, the ultrasound imaging system may analyze the image to ensure the quality is suitable for acquiring HRI measurements and/or guide the user to select suitable ROIs in the image. In some examples, the ultrasound imaging system may sub-divide the acquired image into portions. One or more parameters may be extracted from each portion. In some examples, if the extracted parameter is within a certain range, the image may be determined to have a quality suitable for acquiring HRI measurements. In some examples, the parameters of adjacent portions may be compared. In some examples, if two adjacent portions have parameters of sufficiently similar values, the image may be determined to have a quality suitable for acquiring HRI measurements. If the image is found not to be of suitable quality, the ultrasound imaging system may prompt the user to acquire another image (e.g., via a text warning on display <NUM>). The ultrasound imaging system may then return to the acquisition guidance as described with reference to <FIG>.

<FIG> shows an example image including a portion of a liver and a kidney subdivided into portions according to principles of the present disclosure. Image <NUM> includes a portion of a liver <NUM>, a portion of a kidney <NUM>, and a portion of the hepatorenal interface <NUM>. As described, one or more processors, such as image processor <NUM>, may segment the image <NUM> and/or fit a curve <NUM> to the hepatorenal interface <NUM>. Based at least in part, on the segmentation and/or curve <NUM>, the one or more processors may determine an upper boundary <NUM> of the kidney <NUM> and a lower boundary <NUM> of the kidney <NUM>. The region between the upper boundary <NUM> and lower boundary <NUM> of the kidney <NUM> may be divided into multiple sub-bands (e.g., depth bands) <NUM>. In some examples, the width of the sub-bands may be approximately <NUM>-<NUM>. One or more parameters of pixels within each sub-band may be determined (e.g., intensity distribution, average intensity, standard deviation of intensity, signal-to-noise ratio, etc.). In some examples, if the parameter of one or more of the sub-bands is within an acceptable range, the image <NUM> may be determined to be of suitable quality for acquiring HRI measurements. In some examples, the parameter of one sub-band may be compared to the parameter of one or more adjacent sub-bands. In some examples, if two adjacent sub-bands have parameters that are sufficiently similar (e.g., within <NUM>%, within <NUM>%), then the image may be determined to have a quality suitable for acquiring HRI measurements.

In some examples, the ultrasound imaging system may divide the sub-bands into sub-lengths and extract parameters of the pixels from at least one sub-length from each sub-band. <FIG> shows an example image including a portion of a liver and a kidney subdivided into portions according to principles of the present disclosure. Image <NUM> includes a portion of a liver <NUM>, a portion of a kidney <NUM>, and a portion of the hepatorenal interface <NUM>. As described, one or more processors, such as image processor <NUM>, may segment the image <NUM> and/or fit a curve <NUM> to the hepatorenal interface <NUM>. Based at least in part, on the segmentation and/or curve <NUM>, the one or more processors may divide a portion of the image <NUM> from the upper bound of the kidney <NUM> to the lower bound of the kidney <NUM> into sub-lengths. Dashed lines <NUM> define a first sub-length <NUM> on a liver <NUM>-side of the hepatorenal interface <NUM> and a second sub-length <NUM> on a kidney <NUM>-side of the hepatorenal interface <NUM>.

In some examples, a parameter may be extracted from sub-lengths <NUM>, <NUM> for each sub-band (not shown in <FIG>, see <FIG>). That is, not all of the pixels included in an entire sub-band may be used to extract the parameter, rather only those pixels included in the sub-length may be used. In some examples, two parameter values may be extracted for each sub-band. For example, a value of a parameter may be extracted for sub-length <NUM> of a sub-band and another value of the parameter may be extracted for sub-length <NUM> of the sub-band. In some examples where parameters of adjacent sub-bands are compared, the values of the parameters for sub-length <NUM> may be compared to one another and the values of parameters for sub-length <NUM> may be compared to one another.

In some examples, a width of the second sub-length <NUM> may be based, at least in part, on a width of the renal cortex <NUM> of the kidney <NUM>. In some examples, the widths of the first and second sub-lengths <NUM>, <NUM> may be based, at least in part, on a width of the sub-bands such that enough pixels are within each sub-length of each sub-band to extract a parameter from each sub-length of each sub-band. For example, a portion of an image within a sub-length of a sub-band may be approximately <NUM>-<NUM> by <NUM>-<NUM>.

<FIG> shows example plots of values of a parameter extracted from an image according to principles of the present disclosure. Plots <NUM> and <NUM> show distributions of intensities of pixels of different sub-bands of an image, such as image <NUM> and/or image <NUM>. In plot <NUM>, each curve is the intensity distribution of pixels for a different sub-band (e.g., sub-bands <NUM>) of a sub-width associated with the liver (e.g., sub-width <NUM>). In plot <NUM>, each curve is the intensity distribution of pixels for a different sub-band (e.g., sub-bands <NUM>) of a sub-width associated with the kidney (e.g., sub-width <NUM>). The fifth band is the sub-band closest to the bottom of the kidney (e.g., adjacent to line for lower boundary <NUM>) and the first sub-band is the sub-band closest to the top of the kidney (e.g., adjacent to line for upper boundary <NUM>).

In both plot <NUM> and <NUM>, the curves for each sub-bands is near-Gaussian, and there is a gradual shift in the peaks due to attenuation as depth increases. However, there is not a significant change in width of the distribution or shift in the peak between adjacent sub-bands. Thus, the extracted parameters of each sub-band suggest the image is of suitable quality for acquiring HRI measurements. In some examples, a cross-correlation coefficient (CCC) may be calculated for two adjacent curves. The CCC may be compared to a threshold value to determine if the adjacent sub-bands are sufficiently similar. For example, the maximal value of the CCC may be one (<NUM>) and the sub-bands may be found sufficiently similar if the CCC is greater than or equal to <NUM>.

If one or more of the curves had been non-Gaussian, a low CCC, and/or a significant shift occurred between peaks of adjacent sub-bands, it suggests that the image may not be of suitable quality for HRI measurements. For example, a significant shift in the peak intensity may suggest the presence of a blood vessel or cyst in a sub-band. In another example, a non-Gausian distribution may suggest an image artifact that may affect the HRI measurements.

While the example shown in <FIG> shows intensity distributions of pixels, other parameters may be extracted from the sub-bands and/or sub-widths of the sub-bands in other examples. For example, the SNR, and/or average pixel intensity may be computed. In some examples, rather than comparing the parameters of the sub-bands to one another, an average of the extracted parameters may be calculated to determine if the image is of suitable quality. In some examples, a weighted average may be used. In some examples, the sub-band closest to the bottom of the kidney and the sub-band closest to the top of the kidney may be ignored and/or given less weight as these bands are less likely to be used for acquiring HRI measurements. If, based on the extracted parameters, it is determined the image is not of suitable quality, the ultrasound imaging system may prompt the user to acquire a new image.

In some examples, the parameters extracted from the sub-bands may be used to evaluate each sub-band individually for suitability for acquiring HRI measurements. For example, if the SNR of a particular sub-band does not meet a threshold value, the ultrasound imaging system may provide an indication to the user that the particular sub-band should not be used to select a ROI for HRI measurements rather than requiring the user to acquire a new image.

If the image is found to be of suitable quality for acquiring HRI measurements, the ultrasound imaging system may provide guidance, such as visual cues, to the user for selecting appropriate ROIs for calculating the HRI.

Returning to <FIG>, in some examples, a display, such as display <NUM>, may provide graphic overlays corresponding to curve <NUM>, lines <NUM>, <NUM>, and/or lines demarcating sub-bands <NUM>. Optionally, the display may provide graphic overlays corresponding to the sub-widths <NUM> and <NUM>. In some examples, the display information for the graphic overlays may be provided by one or more processors, such as graphic processor <NUM> and/or image processor <NUM>. By providing the sub-bands <NUM> on the display, the user may be guided to properly select ROIs at a same depth. By providing the curve <NUM>, the user may be guided to properly select one ROI on the liver <NUM>, such as example liver ROI <NUM>, and one ROI on the kidney <NUM>, such as example ROI <NUM>. By providing the sub-width <NUM>, the user may be guided to properly place ROI <NUM> on the renal cortex rather than another portion of the kidney <NUM>. By providing sub-width <NUM>, the user may be guided to select a portion of the liver <NUM> near the kidney <NUM>.

As noted with reference to <FIG>, optionally, in some examples, the display may provide graphical overlays (not shown) that indicate certain sub-bands should not be used for placing ROIs <NUM>, <NUM>. Examples include, but are not limited to, hash marks, "greying out" the sub-band, and/or text "DO NOT USE" over the sub-band.

Optionally, in some examples, text and/or other guidance may be provided to the user on the display. For example, a text warning may appear if the user places the ROIs <NUM>, <NUM> in different sub-bands and/or outside the sub-widths. In another example, one or both of the ROIs <NUM>, <NUM> may change color when one is placed in a different sub-band and/or outside a sub-width. In other examples, the system may not permit the user to place the ROIs in different sub-bands and/or outside the appropriate sub-widths. In some examples, the user may select whether sub-bands, sub-widths, and/or other visual cues for selecting the ROIs are provided on the display by providing inputs via a user interface, such as user interface <NUM>.

<FIG> shows example regions of interest according to principles of the present disclosure. Image <NUM> is a ROI of a liver, which may have been acquired from an image, such as image <NUM> and/or image <NUM>. Image <NUM> is a ROI of a kidney, which may have been acquired from an image, such as image <NUM> and/or image <NUM>. In some examples, image <NUM> may correspond to ROI <NUM> and image <NUM> may correspond to ROI <NUM>. The HRI measurement may be calculated based, at least in part, on image <NUM> and image <NUM>. Typically the HRI is determined by calculating an average intensity of image <NUM> and calculating an average intensity of image <NUM>. The average intensity of image <NUM> is divided by the average intensity of image <NUM> to arrive at the HRI.

Thus, as disclosed herein, at a first stage, a user may be guided to acquire an image at a suitable imaging plane. For example, by providing guidance related to the angle of the hepatorenal interface and/or a location of the hepatorenal interface within a centrally located bounding box. Optionally, additional guidance may be provided based on the average intensity of pixels of the hepatorenal interface. At a second stage, the image acquired at a suitable imaging plane during the first stage may be assess for quality. In some examples, a portion of the image may be sub-divided into sub-bands, and the assessment may be based on an analysis of at least some of the pixels of individual sub-bands. If the quality is not suitable, the imaging system may return to the first stage. However, once the quality of the image is determined to be suitable, the sub-bands and/or other visual guidance (e.g., sub-widths) may be provided to assist the user to properly place the ROIs on the image. Once the ROIs are placed, the HRI may be calculated.

<FIG> is a flow chart of a method according to principles of the present disclosure. The flow chart 900A provides a technique for providing guidance to a user for acquiring an image at an imaging plane suitable for acquiring HRI measurements. In some examples, the method shown in <FIG> may be performed by an ultrasound imaging system, such as ultrasound imaging system <NUM>. For example, one or more processors of ultrasound imaging system <NUM>, such as image processor <NUM> and graphic processor <NUM>, may execute one or more instructions to perform some or all of the method shown in <FIG>. In some examples, the instructions may be stored on a non-transitory computer readable medium, such as local memory <NUM>.

As indicated at block <NUM>, one or more processors may receive an image. The one or more processors may segment the image do extract a liver region, a kidney region, and a hepatorenal interface as indicated at block <NUM>. The one or more processors may fit a curve to the hepatorenal interface as indicated by block <NUM>. Once the curve is fitted, a midpoint of the curve may be calculated to find a location of an anchor point as indicated by block <NUM>. Based, at least in part, on the curve and the anchor point, the one or more processors may determine a tangent line to the curve at the anchor point as indicated by block <NUM>. A horizontal line at the anchor point may also be determined by the one or more processors as indicated by block <NUM>.

As indicated by block <NUM>, the one or more processors may calculate an angle between the tangent line and the horizontal line. In some examples, the suitability of the image may be based, at least in part, on a comparison of the angle to a threshold value (e.g., <NUM> degrees).

As indicated by block <NUM>, the currently acquired image may be displayed (e.g., on display <NUM>). A visual cue may also be displayed as a graphical overlay on the image as indicated by block <NUM>. In some examples, the visual cue is based, at least in part the tangent line and the angle between the tangent line and the horizontal line. In some examples, the visual cue may include the anchor point, the tangent line, and/or the horizontal line. In some examples, an indicator of the angle may also be displayed, such as indicator <NUM>. In some examples, a bounding box, such as bounding box <NUM>, may be displayed in a central portion of the image may be displayed. This may assist the user in acquiring the image at a suitable imaging plane for acquiring HRI measurements. Of course, it is understood that the operations performed at blocks <NUM>-<NUM> may be performed continuously and/or repeatedly as the user moves the ultrasound probe and new images are acquired by the ultrasound imaging system.

<FIG> is a flow chart of a method according to principles of the present disclosure. The method shown in flow chart 900B may provide a technique for guiding a user in selecting appropriate ROIs as well as determining suitability of the image for HRI measurements. In some examples, the method shown in <FIG> may be performed by an ultrasound imaging system, such as ultrasound imaging system <NUM>. For example, one or more processors of ultrasound imaging system <NUM>, such as image processor <NUM> and graphic processor <NUM>, may execute one or more instructions to perform some or all of the method shown in <FIG>. In some examples, the instructions may be stored on a non-transitory computer readable medium, such as local memory <NUM>. In some examples, the method shown in <FIG> may be performed after the method shown in <FIG> is performed.

As indicated by block <NUM>, one or more processors may determine upper and lower boundaries of the kidney region in an image. The one or more processors may divide the region between the boundaries into multiple sub-bands as indicated by block <NUM>. In some examples, the one or processors may extract a parameter from at least some of the pixels of each of the sub-bands, or at least some of the sub-bands, as indicated by block <NUM>. In some examples the one or more processors may further divide the sub-bands into sub-widths, such as sub-widths <NUM> and <NUM> and parameters may be extracted from the sub-widths of the sub-bands. The one or more processors may determine whether the image is of suitable quality based, at least in part, on the parameters as indicated by block <NUM>. In some examples, the image is determined to be of suitable quality based, at least in part, on a comparison of parameters of adjacent sub-bands to one another. In some examples, the image is determined to be of suitable quality based, at least in part, on a comparison of one or more of the parameters to one or more threshold values.

The sub-bands and/or sub-widths may be displayed as graphical overlays on the image as indicated by block <NUM>. The sub-bands and/or sub-widths provided on the display may guide the user to place ROIs in appropriate regions of the liver and kidney. The graphical overlays may further guide the user to place the ROIs at the same depth. The one or more processors may receive a user input (e.g., via a user interface, such as user interface <NUM>) indicating ROIs as indicated by blocks <NUM> and <NUM>. Based, at least in part, by pixels located in the ROIs, the one or more processors may calculate the HRI as indicated by block <NUM>. In some examples, the HRI may be provided as text on the display with the image.

<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 and/or controllers described herein, for example, image processor <NUM> shown in <FIG> and/or any other processor or controller 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 embodiments, 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 embodiments the registers <NUM> may be implemented using static memory. The register may provide data, instructions and addresses to the core <NUM>.

In some embodiments, 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 embodiments, 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 memory <NUM> may communicate with controller <NUM> and core <NUM> via internal connections 1020A, 1020B, 1020C and 1020D. 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 memory <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 embodiments, the external memories may be included in a system, such as ultrasound imaging system <NUM> shown in <FIG>, for example local memory <NUM>.

The systems, methods, and apparatuses disclosed herein may provide scanning or imaging plane identification technique and/or ultrasound image quality control technique that can be utilized in general liver imaging where HRI measurements are desired which may reduce workload for busy ultrasound users in some examples. In some examples, the systems, methods, and apparatuses may be implemented on an ultrasound imaging system that provides a raw data/RF signal and/or DICOM images. In some examples, the systems, methods, and apparatuses may be included as a component of computer-aided diagnosis (CAD) system to assist doctors in liver ultrasound study determine key parameter measurements and reporting.

Although described with reference to live imaging, the techniques described herein may be applied to previously acquired images, such as DICOM images stored in a picture archiving and communication system (PACS). For example, pre-acquired images may be segmented and analyzed as described with reference to <FIG>, and if the angle is found suitable, the pre-acquired image may be analyzed as described with reference to <FIG>. If the pre-acquired image is suitable for acquiring HRI measurements, the user may be guided to properly select ROIs and the HRI measurement may be computed as described with reference to <FIG> and <FIG>.

In various embodiments 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++", "C#", "Java", "Python", 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 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 instruction to perform the functions described herein.

Claim 1:
An ultrasound imaging system (<NUM>) configured to provide user guidance for acquiring images suitable for hepato-renal index measurements, the system comprising:
a non-transitory computer readable medium (<NUM>) encoded with instructions; and
at least one processor (<NUM>) in communication with the non-transitory computer readable medium and configured to execute the instructions, wherein when executed, the instructions cause the at least one processor to:
segment a liver region, a kidney region, and a hepatorenal interface from an image;
fit a curve to the hepatorenal interface;
calculate an anchor point at a midpoint of the curve;
determine a tangent line to the curve at the anchor point;
determine a horizontal line at the midpoint;
calculate an angle between the tangent line and the horizontal line; and
generate a visual cue for display, wherein the visual cue is based, at least in part, on the tangent line and the angle between the tangent line and the horizontal line; and
a display (<NUM>) configured to display the image and the visual cue as a graphical overlay over the image.