A system and method for providing user guidance for obtaining hepatic and renal index measurements.

Abstract

Guidance is provided to the user, at least in part, by a graphical overlay on the display of the ultrasound image. The guidance aids the user in acquiring an appropriate image for making a measurement of the Hepatic-Renal Index (HRI). In some examples, the guidance aids the user in locating an appropriate imaging plane that includes a portion of the liver and kidney. In some examples, the guidance further aids the user in properly locating a region of interest within the image for calculating the HRI, such as at the same depth and appropriate portion of the liver and kidney. In some examples, one or more processors analyze the image to ensure that the image quality is adequate for calculating the HRI.

Description

Technical Field

[0001]

[0001] This application relates to providing user guidance for obtaining liver and kidney index measurement values. More specifically, this application relates to providing guidance for selecting an imaging plane and a region of interest for calculating liver and kidney indices.

Background Art

[0002]

[0002] Non-alcoholic fatty liver disease (NAFLD) has become one of the major causes of liver diseases due to the high morbidity of obesity and diabetes. Its incidence has been steadily increasing and affects approximately 25% - 30% of the population in Western countries and developing countries. The clinical term for fatty liver is hepatic steatosis, which is defined as an excessive accumulation of fat as triglycerides in liver cells (about 5% - 10% of body weight). The early stage of hepatic steatosis is symptomless and can be reversed by simple lifestyle changes, such as through regular exercise and a healthy diet. Hepatic steatosis can turn into more advanced liver diseases, such as non-alcoholic steatohepatitis (NASH) and liver fibrosis. If left untreated at these stages, fatty liver progresses to end-stage diseases including cirrhosis and primary hepatocellular carcinoma.

[0003]

[0003] In current clinical practice, the optimal criterion for fatty liver diagnosis is liver biopsy, which is an invasive procedure with room for sampling error and interpretive variability. Magnetic resonance proton density fat fraction measurement (MR-PDFF) is considered a new reference standard for NAFLD diagnosis because it can provide a quantitative biomarker of liver fat content. However, MR-PDFF is an expensive diagnostic instrument that is not always available, especially in small hospitals. Compared with magnetic resonance imaging (MRI), ultrasound is a widely available and cost-effective imaging modality. Therefore, ultrasound is more suitable for screening and / or diagnosis of low-risk general population groups.

[0004]

[0004] An ultrasound-based method called the hepatorenal index (HRI) has been used clinically to detect fatty liver. Excessive fat infiltration in the liver increases the acoustic backscatter coefficient, resulting in higher grayscale values ​​in ultrasound B-mode imaging. Under normal conditions, the liver parenchyma and the renal cortex (RC) of the kidney have similar echointensity. With more fat deposition, the liver appears to have higher echointensity (i.e., brighter) than the RC. HRI is often calculated as the ratio of the liver's echointensity to that of the RC. Based on B-mode data, the echointensities from the liver and kidney are estimated by selecting a region of interest (ROI) within the liver parenchyma and the RC at a similar depth, and then averaging the grayscale echointensity values ​​in the ROI. However, HRI can have reliability issues that limit its applicability due to user error. For example, a user may not acquire images from a screen containing sufficient tissue in both the liver and kidney, or may select an ROI in the kidney that is at a different depth than the ROI in the liver. Therefore, improved techniques for obtaining HRIs that are less likely to cause user errors are desired. [Overview of the project] [Problems that the invention aims to solve]

[0005]

[0005] Systems, apparatus, and methods are disclosed for guiding a user to acquire images on an appropriate screen and to select ROIs at the same depth in the liver and kidneys. In some examples, the images and / or selected ROIs are analyzed to ensure they are of sufficient quality to calculate the HRI. If the quality of the selected ROIs is insufficient, the user is prompted to select a new ROI and / or acquire a new image. [Means for solving the problem]

[0006]

[0006] According to at least one example disclosed herein, an ultrasound imaging system is configured to provide user guidance for acquiring an image suitable for measuring the hepatorenal index, the ultrasound imaging system comprising a non-temporary computer-readable medium encoded with instructions and at least one processor communicating with the non-temporary computer-readable medium and executing instructions, the instructions which, when executed, cause the at least one processor to segment the image into liver regions, kidney regions and the hepatorenal interface, fit a curve to the hepatorenal interface, calculate anchor points at the midpoints of the curve, determine tangents to the curve at the anchor points, determine a horizontal line at the midpoints, calculate an angle between the tangent and the horizontal line, and generate a visual cue for display, at least partially based on the tangent and the angle between the tangent and the horizontal line. The ultrasound imaging system comprises a display that displays the image and the visual cue as a graphical overlay on the image.

[0007]

[0007] According to at least one example disclosed herein, a method for providing user guidance for obtaining an image suitable for measuring the hepatorenal index includes the steps of: receiving an image; segmenting the image into liver regions, kidney regions and the hepatorenal interface; fitting a curve to the hepatorenal interface; calculating anchor points at the midpoint of the curve; determining tangents to the curve at the anchor points; determining a horizontal line at the midpoint; calculating an angle between the tangent and the horizontal line; displaying the image; and displaying a visual cue as a graphical overlay on the image, at least partially based on the tangent and the angle between the tangent and the horizontal line. [Brief explanation of the drawing]

[0008] [Figure 1]

[0008] This is a block diagram of an ultrasonic imaging system configured according to the principles of the present disclosure. [Figure 2]

[0009] This is an illustrative image, including a portion of the liver and kidney, based on the principles of this disclosure. [Figure 3]

[0010] This is an illustrative image including portions of the liver and kidney with curves adapted to the interface, based on the principles of this disclosure. [Figure 4A]

[0011] This is an exemplary image on a display, accompanied by a graphical overlay to provide guidance to the user, based on the principles of this disclosure. [Figure 4B] This is an exemplary image on a display, accompanied by a graphical overlay to provide guidance to the user, based on the principles of this disclosure. [Figure 5]

[0012] This is an exemplary image showing a portion of the liver and kidney subdivided into multiple parts, based on the principles of this disclosure. [Figure 6]

[0013] This is an exemplary image showing a portion of the liver and kidney subdivided into multiple parts, based on the principles of this disclosure. [Figure 7]

[0014] This is an illustrative plot of parameter values ​​extracted from an image according to the principle of this disclosure. [Figure 8]

[0015] This is an exemplary area of ​​interest based on the principles of this disclosure. [Figure 9A]

[0016] This is a flowchart of the method based on the principles of this disclosure. [Figure 9B]

[0017] This is a flowchart of the method based on the principles of this disclosure. [Figure 10]

[0018] This is a block diagram illustrating an exemplary processor based on the principles of this disclosure. [Modes for carrying out the invention]

[0009]

[0019] The following descriptions relating to exemplary examples are, by their very nature, illustrative and are not intended in any way to limit the Disclosure or its application or use. The following detailed descriptions relating to examples of the System and Method refer to the accompanying drawings, which form part of this Specification, illustrating specific examples in which the described System and Method are put into practice. These examples are described in sufficient detail to enable a person skilled in the art to put the System and Method disclosed herein into practice, and it should be understood that other examples may be used, and that structural and logical modifications may be made without departing from the spirit and scope of this Disclosure. Furthermore, for clarity, detailed descriptions of certain features are not discussed where they are obvious to a person skilled in the art, so as not to obscure the description of this Disclosure. Therefore, the following detailed descriptions should not be construed as limiting, and the scope of the System and Method is defined solely by the accompanying claims.

[0010]

[0020] The hepatorenal index (HRI) is typically obtained based on the pixel intensity of B-mode images displayed in an ultrasound imaging system. When measured properly, HRI is a useful diagnostic indicator for fatty liver disease. The reliability of HRI is compromised by the acquisition of poor images and / or by the inappropriate selection of regions of interest (ROIs) in the liver and / or kidneys.

[0011]

[0021] During liver imaging for which an HRI measurement is desired, the liver and kidney should be imaged in an imaging plane that provides a sufficient portion of the liver on one side of the image (typically the left side of the image in the system according to the present invention) and a sufficient portion of the kidney on the other side of the image (typically the right side of the image in the system according to the present invention) for ROI selection in each organ. Furthermore, the imaging plane should be such that sufficient portions of both the liver and kidney are at similar imaging depths (preferably the same imaging depth). That is, the liver and kidney should appear nearly side by side rather than overlapping perpendicularly to the imaging beam. However, in practice, the view of the liver and kidney is limited due to the ribs. Typically, a two-dimensional (2D) ultrasound image is obtained at a specific anatomical location and a specific scanning angle. For example, an image of the hepatorenal interface in Morrison's pouch is obtained. After the image of the hepatorenal interface is obtained, the probe is rotated slightly to obtain the desired image of the liver and kidney nearly side by side for HRI measurement.

[0012]

[0022] If the interface between the liver and kidney (hepatorenal interface) is horizontal or nearly horizontal in the image (e.g., perpendicular or nearly perpendicular to the beam direction), effective depth information of the kidney may be lacking in the ultrasound image, and it may not be a reliable criterion for calculating HRI. A higher angle at the liver-kidney interface with respect to the horizontal line (e.g., a straight line perpendicular to the beam direction) may provide better effective depth information for the kidney. However, due to anatomical structures that limit the field of view of the ribs and other ultrasound probes, the angle at the liver-kidney interface can actually be limited to a range of zero to several tens of degrees (e.g., 40 degrees, 50 degrees, etc.) during examinations.

[0013]

[0023] Due to the anatomical reality that imposes physical constraints on the placement and orientation of the ultrasonic probe, obtaining an appropriate image for HRI calculation requires a significant amount of time and / or a skilled sonographer. Further, even if an image is obtained, significant time and skill are still required to determine an appropriate ROI in the image for use in HRI. Therefore, a technique to assist the ultrasonic user in obtaining an appropriate image and an appropriate ROI is desired.

[0014]

[0024] The present disclosure is directed to a system and method for guiding a user to select an acceptable imaging plane by providing visual cues as graphical overlays on an image during scanning on a display of an ultrasonic imaging system. For example, the visual cue includes an indication of the angle of a straight line contacting the liver-kidney interface. After the image is acquired, the statistical properties in different depth bands of the acquired image are evaluated to confirm that the acquired image is suitable for calculating HRI measurements. In some examples, a graphical indication of the depth band is provided on the display to assist the user in selecting two ROIs at the same depth in the liver and kidney. In some applications, the reliability and reproducibility of the HRI measurements are improved. In some applications, the workflow for obtaining HRI measurements is improved. In some applications, the time and / or skill required for the user to obtain HRI measurements is reduced.

[0015]

[0025] FIG. 1 shows a block diagram of an ultrasonic imaging system 100 constructed in accordance with the principles of the present disclosure. The ultrasonic imaging system 100 according to the present disclosure includes a transducer array 114, which is included in an ultrasonic probe 112, such as an external probe or an internal probe. The transducer array 114 is configured to transmit ultrasonic signals (e.g., beams, waves) and receive echoes in response to the ultrasonic signals. A variety of transducer arrays are used, such as linear arrays, curved arrays, or phased arrays. The transducer array 114 includes a two-dimensional array of transducer elements (as shown) capable of scanning in both the height and azimuth dimensions, for example, for 2D and / or 3D imaging. As is generally known, the axial direction is normal to the plane of the array (in the case of a curved array, the axial direction diverges), the azimuth direction is generally defined by the longitudinal dimension of the array, and the height direction is the direction transverse to the azimuth direction.

[0016]

[0026] In some embodiments, the transducer array 114 is coupled to a microbeamformer 116, which is disposed in the ultrasonic probe 112 and controls the transmission and reception of signals by the transducer elements in the array 114. In some embodiments, the microbeamformer 116 controls the transmission and reception of signals by the active elements in the array 114 (e.g., an active subset of the elements of the array that define an active aperture at any given time).

[0017]

[0027] In some embodiments, the microbeamformer 116 is coupled to a transmit / receive (T / R) switch 118, for example, by a probe cable or wirelessly, which switches between transmit and receive to protect the main beamformer 222 from high-energy transmit signals. In some embodiments, such as a portable ultrasound system, the T / R switch 118 and other elements in the system may be contained within the ultrasound probe 112 rather than inside the ultrasound system body housing the image processing electronics. The ultrasound system body typically includes software and hardware components, including executable instructions that provide circuit configurations and user interfaces for signal processing and image data generation (e.g., processing circuit configuration 150 and user interface 124).

[0018]

[0028] The transmission of ultrasonic signals from the transducer array 114 under the control of the microbeamformer 116 is directed by a transmit controller 120 coupled to the T / R switch 118 and the main beamformer 122. The transmit controller 120 controls the direction in which the beam is directed. The beam is directed linearly (orthogonally) from the transducer array 114, or at several different angles for a wider field of view. The transmit controller 120 is also coupled to a user interface 124, which receives input from user operation of user controls. The user interface 124 includes one or more input devices, such as a control panel 152, which includes one or more mechanical controls (e.g., buttons, encoders, etc.), touch-sensitive controls (e.g., trackpads, touchscreens, etc.), and / or other known input devices.

[0019]

[0029] In some embodiments, the partially beamformed signal generated by the microbeamformer 116 is coupled to the main beamformer 122, where the partially beamformed signals from individual patches of transducer elements are combined to form a fully beamformed signal. In some embodiments, the microbeamformer 116 is eliminated, and the transducer array 114 is under the control of the main beamformer 122, which performs all beamforming of the signal. In embodiments with and without the microbeamformer 116, the beamformed signal from the main beamformer 122 is coupled to a processing circuit configuration 150, which includes one or more processors (e.g., a signal processor 126, a B-mode processor 128, a Doppler processor 160, and one or more image generation and processing components 168) configured to create an ultrasound image from the beamformed signal (e.g., beamformed RF data).

[0020]

[0030] The signal processor 126 is configured to process the received beamformed RF data in various ways, including bandpass filtering, decimation, I and Q component separation, and harmonic signal separation. The signal processor 126 also performs additional signal enhancement, such as speckle reduction, signal synthesis, and noise reduction. The processed signal (also referred to as the I and Q components of the IQ signal) is coupled to additional downstream signal processing circuits for image generation. The IQ signal is coupled to multiple signal paths within the system, each of which is associated with a specific array 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 includes a B-mode signal path 158 that couples the signal from the signal processor 126 to a B-mode processor 128 that generates B-mode image data.

[0021]

[0031] The B-mode processor can use amplitude detection for imaging structures in the body. The signals generated by the B-mode processor 128 are coupled to the scanning converter 130 and / or the multi-section reformatter 132. The scanning converter 130 is configured to arrange the echo signals into a desired image format based on the spatial relationship in which they are received. For example, the scanning converter 130 arranges the echo signals into a two-dimensional (2D) sector format, or into a three-dimensional (3D) format of a pyramidal or other shape. The multi-section reformatter 132 can convert echoes received from points in a common plane in a volume region of the body into an ultrasound image (e.g., a B-mode image) of that plane, as described, for example, in U.S. Patent No. 6,443,896 (Detmer). In some embodiments, the scanning converter 130 and the multi-section reformatter 132 may be implemented as one or more processors.

[0022]

[0032] The volume renderer 134 generates an image (also referred to as projection, render, or rendering) of a 3D dataset viewed from a given reference point, as described in U.S. Patent No. 6,530,885 (Entrekin et al.). In some embodiments, the volume renderer 134 may be implemented as one or more processors. The volume renderer 134 generates renders, such as positive renders or negative renders, by any known or future known technique, such as surface rendering and maximum intensity rendering.

[0023]

[0033] In some embodiments, the system includes a Doppler signal path 162 that couples the output from a signal processor 126 to a Doppler processor 160. The Doppler processor 160 is configured to estimate the Doppler shift and generate Doppler image data. The Doppler image data includes color data which is then overlaid with B-mode (i.e., grayscale) image data for display. The Doppler processor 160 is configured to remove unwanted signals (i.e., noise or clutter associated with non-moving tissue) by filtering, for example, using a wall filter. The Doppler processor 160 is further configured to estimate velocity and power according to known techniques. For example, the Doppler processor includes a Doppler estimator, such as an autocorrelationr, in which case the estimation of velocity (Doppler frequency, spectral Doppler) is based on the argument of the autocorrelation function at lag-1, and the estimation of Doppler power is based on the magnitude of the autocorrelation function at lag-zero. Furthermore, motion can also be estimated by known phase-domain (e.g., parametric frequency estimators such as MUSIC and ESPRIT) or time-domain (e.g., cross-correlation) signal processing techniques. The velocity and / or power estimates are then mapped to a desired range of display colors according to a color map. The color data, also referred to as Doppler image data, is then coupled to a scanning converter 130, where the Doppler image data is converted to a desired image format so as to form a color Doppler or power Doppler image and overlaid onto a B-mode image of the tissue structure.

[0024]

[0034] The outputs from the scanning converter 130, the multi-planar reformatter 132, and / or the volume renderer 134 are coupled to the image processor 136 for further enhancement, buffering, and temporary storage before being displayed on the image display 138. The graphics processor 140 generates graphic overlays for display with the images. These graphic overlays include standard identification information such as patient name, image date and time, and imaging parameters. For these purposes, the graphics processor 140 is configured to receive input such as typed patient name or other annotations from the user interface 124. The user interface 124 can also be coupled to the multi-planar reformatter 132 for the selection and control of the display of multiple multi-planar reconstructed (MPR) images.

[0025]

[0035] System 100 includes local memory 142. Local memory 142 is implemented as any suitable non-temporary computer-readable medium (e.g., flash drive, disk drive). Local memory 142 stores data generated by System 100, including ultrasound images, executable instructions, patient medical history, or any other information necessary for the operation of System 100. In some examples, local memory 1242 includes multiple memories, which may be the same or different types. For example, local memory 142 includes dynamic random access memory (DRAM) and flash memory.

[0026]

[0036] As described above, system 100 includes a user interface 124. The user interface 124 includes a display 138 and a control panel 152. The display 138 includes a display device implemented using various known display technologies, such as LCD, LED, OLED, or plasma display technology. In some embodiments, the display 138 may comprise multiple displays. The control panel 152 is configured to receive user input (e.g., inspection type, image frame storage, window freezing, ROI selection). The control panel 152 includes one or more hardware controls (e.g., buttons, knobs, dials, encoders, mice, trackballs, etc.). In some embodiments, the control panel 152 additionally or alternatively includes software controls (e.g., GUI control elements, or simply GUI controls provided on a touch-sensitive display). In some embodiments, the display 138 may be a touch-sensitive display that includes one or more software controls of the control panel 152.

[0027]

[0037] The components of System 100 shown in Figure 1 may not include all of the components of System 100. For example, System 100 includes one or more processors that implement an operating system for the system, providing the GUI elements described herein. In other examples, System 100 includes various interfaces for receiving or transmitting information wirelessly or via wired connections, such as transmitting acquired images to a photo archiving and communications system (PACS) and receiving electronic medical records from a hospital server.

[0028]

[0038] In some embodiments, the various components shown in Figure 1 may be combined. For example, the multi-section reformatter 132 and the volume renderer 134 may be implemented as a single processor. In some embodiments, the various components shown in Figure 1 may be implemented as separate components. For example, the signal processor 126 may be implemented as multiple separate processors for each imaging mode (e.g., B-mode, Doppler). In other examples, the image processor 136 may be implemented as multiple separate processors for different tasks and / or parallel processing of the same task. In some embodiments, one or more of the various processors shown in Figure 1 may be implemented by a general-purpose processor and / or microprocessor configured to perform a specific task. In some examples, the processor may be configured by providing instructions for the task from a non-temporary computer-readable medium (e.g., from local memory 142). These instructions are then executed by the processor. In some embodiments, one or more of the various processors may be implemented by application-specific circuitry. In some embodiments, one or more of the various processors (e.g., image processor 136) may be implemented using one or more graphical processing units (GPUs).

[0029]

[0039] In some cases, the user provides user input via the user interface 124 when an HRI measurement is desired for a subject. For example, the user selects the HRI option from the operating system menu of system 100. Optionally, system 100 may import the subject's medical records (e.g., from a hospital information system (HIS)) to confirm that the subject does not have any chronic kidney disease or coexisting kidney and liver disease that would make them unsuitable for HRI measurement. Alternatively, system 100 may prompt the user to check the subject's medical records to confirm that the subject is suitable for HRI measurement. If the subject is unsuitable for HRI measurement, a different technique for evaluating NAFLD may be applied to that subject. Other techniques include different ultrasound techniques (e.g., machine learning-based analysis) and / or other imaging modalities (e.g., MRI).

[0030]

[0040] The imaging system 100 provides the user with guidance for acquiring an imaging plane suitable for obtaining HRI measurements. The user acquires initial images of the liver and kidney (or parts thereof). The imaging system 100 determines the location of the hepatorenal interface (e.g., the interface) from the initial images, and based at least partially on the curve of the hepatorenal interface, the system 100 provides the user with guidance for acquiring an imaging plane suitable for obtaining HRI measurements. In some examples, this location is determined by one or more processors, such as the image processor 136 of the system 100. This guidance includes one or more visual cues indicating the geometric shape of anatomical features and / or their relative positions, the image frame (e.g., the field of view of the ultrasound probe 112), and / or the ultrasound beam (e.g., the beam provided by the transducer array 114). The visual cues enable the user to visually determine when appropriate parts of the liver and kidney are present in the image and / or when the liver and kidney are in appropriate relative positions in the image. Examples of visual cues include, but are not limited to, anchor points indicating midpoints in the retinoid interface, tangents to the retinoid interface at the midpoints, horizontal lines passing through the midpoints, and / or bounding boxes surrounding the central portion of the image. In some examples, visual cues are provided as graphical overlays on the image. In some examples, this graphical overlay is generated by one or more processors, such as image processor 136 and / or graphics processor 140.

[0031]

[0041] Figure 2 shows an exemplary image including portions of the liver and kidney according to the principles of this disclosure. Image 200 is an ultrasound image including portions of the liver 202 and kidney 204. In some examples, the imaging system 100 determines the location of the interface 206 between the liver 202 and kidney 204 based on an image segmentation technique (e.g., edge detection, machine learning). Alternatively, the location of the interface 206 may be found by a semi-automatic technique. For example, the user provides input via a user interface 124 to indicate one or more seed points 208 along the interface 206. In some examples, such as the example shown in Figure 2, the user provides two to four seed points 208. The imaging system 100 determines the location of the interface 206 based at least in part on these seed points 208 using image segmentation and / or deep learning techniques. In some examples, in addition to determining the location of the interface 206, the imaging system 100 segments the liver 202 and / or kidney 204 from image 200. In some examples, one or more processors in the imaging system 100, such as the image processor 136, determine the location of the interface 206 and / or segment the liver 202 and kidney 204 from the image.

[0032]

[0042] In some examples, the curve is fitted to the interface by one or more processors. Figure 3 shows an exemplary image including portions of the liver and kidney with the curve fitted to the interface according to the principles of this disclosure. Image 300 is an ultrasound image including portions of the liver 302 and kidney 304. At least a portion of the hepatorenal interface 306 is also visible in Image 300. A processor, such as image processor 136, computes an equation that defines the curve 310 fitted to the interface 306. The curve 310 is at least partially based on an automatic or semi-automatic segmentation technique, such as those described with reference to Figure 2, used to determine the location of the interface 306. In some examples, a nonlinear curve fitting technique is used to define the curve 310. The curve 310 is provided to display 138 as an overlay on image 300, while in other examples, the equation that defines the curve 310 is computed and stored in system 100, but the curve 310 does not need to be displayed.

[0033]

[0043] Based at least partially on the hepatorenal interface curve, system 100 provides the user with guidance for obtaining an appropriate imaging plane for acquiring HRI measurements. For example, system 100 provides one or more visual cues on display 138. These visual cues include one or more graphical overlays generated based at least partially on the hepatorenal interface curve.

[0034]

[0044] Figures 4A and 4B show exemplary images on a display with a graphical overlay to provide guidance to the user according to the principles of this disclosure. Display 400 is included in display 138 in some examples. This display provides ultrasound images, such as image 401 in Figure 4A and image 403 in Figure 4B. Both images 401 and 403 include the liver 402, kidney 404, and a portion of the hepatorenal interface 406, the hepatorenal interface 406 being a brighter grayscale area (e.g., a generally whiter line) between the liver 402 and kidney 404. Display 400 further provides visual cues as a graphical overlay at least partially based on the geometric shape of the interface 406 to guide the user to obtain an image suitable for obtaining an HRI measurement. In some examples, the graphical overlay includes anchor points 412, horizontal lines 414, tangents 418, bounding boxes 418, and / or angle indicators 424. Although not shown in Figures 4A and 4B, the graphical overlay may further include curves adapted to the hepatorenal interface 406, such as curve 310 shown in Figure 3.

[0035]

[0045] Images 401 and 403 are segmented, and the curve is fitted to the hepatorenal interface 406 (even if the curve is not displayed), as described with reference to Figures 2 and 3. The midpoint of the curve fitted to the hepatorenal interface 406 is calculated and indicated by anchor point 412. A horizontal line extending through anchor point 412 (e.g., a straight line perpendicular to the central scanning line of the ultrasonic beam emitted by a transducer array such as transducer array 114) is calculated and provided as horizontal line 414. However, in some examples, horizontal line 414 may not be shown on the display. A straight line tangent to the curve fitted to the hepatorenal interface 406 at anchor point 412 is calculated and provided as tangent line 416. Optionally, in some examples, only tangent line 416 is displayed, and anchor point 412 is not provided on the display. The segmentation, curve, anchor point 412, horizontal line 414, and / or tangent line 416 are calculated by one or more processors, such as image processor 136. In some cases, the calculation-based display information is generated by other processors, such as the graphics processor 140.

[0036]

[0046] The angle between the tangent line 416 and the horizontal line 414 is calculated by one or more processors (even if not shown). A larger angle between the tangent line 416 and the horizontal line 414 (for example, a larger slope of the tangent line 416) provides a more suitable image for HRI measurement in some applications because it allows more of the liver 402 and kidney 404 tissue to be at the same depth. As shown in Figure 4A, the angle 420 between the tangent line 416 and the horizontal line 414 in image 401 is larger than the angle 422 in image 403 in Figure 4B. In image 401, a considerable portion of the liver 402 and kidney 404 appear adjacent to each other, whereas in image 403, the liver 402 is overwhelmingly above the kidney 404. Thus, in image 403, there is little to no area where the liver 402 and kidney 404 tissue are at the same depth for calculating the HRI measurement.

[0037]

[0047] By providing a visual cue regarding the angle (and / or slope of the tangent 416) between the tangent 416 and the horizontal line 414, the user can more easily find an image appropriate for the HRI measurement using visual guidance. In some examples, the display 400 displays at least the tangent 414, and in some cases, the anchor point 412 and / or the horizontal line 414 as well, so the user "stares" (i.e., visually estimates) when the appropriate angle is achieved, for example, by visually checking the slope of the tangent to the horizontal. In some examples, the appropriate angle is 30 degrees or greater. In some examples, the numerical value of the angle and / or tangent 416 is provided as text on the display 400 by the angle indicator 412. In addition to or instead of this, a qualitative indicator of the angle and / or slope may be provided by indicator 424. In the examples shown in Figures 4A and 4B, text such as "Good" and "Too Small" is provided. However, other qualitative indicators, such as different colors or shapes, may also be used. Qualitative indicators are based on one or more thresholds. For example, an indicator might be “too small” or red when the angle is less than 30 degrees, and “good” or green when the angle is greater than 30 degrees. In some examples, the angle indicator 424 is “built in” into one of the other graphic overlays. For example, the tangent line 416 changes color from one to another when the appropriate angle is achieved. Visual cues to guide the user may be provided in various other ways, such as 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 line is equal to or greater than the minimum threshold angle.

[0038]

[0048] In addition to the appropriate angle, in some examples, the user may be guided to maintain the midpoint of the hepatorenal interface 406 near the center of images 401, 403, as indicated by anchor point 412. This helps ensure that a sufficient portion is visible to obtain HRI measurements of the liver 402 and kidney 404. In the examples shown in Figures 4A and 4B, a bounding box 418 is displayed to guide the user to properly position anchor point 412 in the image. The position of the bounding box 418 is determined based on the midpoint of images 401, 403. The width of the bounding box 418 is based at least partially on the width of images 401, 403. For example, the bounding box 418 is sized to include approximately 5-20% of the scan lines / columns of pixels in images 401, 403. In some examples, the bounding box 418 and / or anchor point 412 change color from one to another when anchor point 412 moves outside the bounding box 418. In some examples, the display 400 provides a textual warning that anchor point 412 is outside the bounding box 418. Optionally, in examples where anchor point 412 and / or bounding box 418 are not provided on the display, the tangent line 416 changes color and / or texture (e.g., from solid to dashed) when the midpoint of the vital interface 406 moves outside the central region of images 401, 403 defined by the bounding box 418 (even if not displayed).

[0039]

[0049] After the midpoint of the hepatic-renal interface 406 is in the appropriate position (for example, anchor point 412 is inside the bounding box 418) and at the appropriate angle (for example, an angle of 30 degrees, or greater than the distance between the tangent 416 and the horizontal line 414), the imaging plane is suitable for acquiring HRI measurements. The user saves the image (for example, image 401) to local memory 142, for example.

[0040]

[0050] Figures 4A and 4B show the display of anchor point 412, horizontal line 414, tangent line 416, bounding box 418, and angle indicator 424, but in other examples only a portion of the graphical overlay may be provided. As mentioned, in some examples only the tangent line 416 is provided. In some examples only the angle indicator 424 is provided. In some examples only the tangent line 416 and the angle indicator 424 are provided. Other combinations of visual cues may also be used. In some examples the user can select which visual cues are provided by providing input, for example, via user interface 124.

[0041]

[0051] Optionally, in some embodiments, the average intensity of pixels in the hepatorenal interface 406 is calculated by one or more processors. If the average intensity is too high, it indicates that the echo intensity of the kidney 404, particularly the RC of the kidney 404, is too low to obtain an HRI measurement. In some examples, the width of the hepatorenal interface 406 is approximately 3 to 5 pixels. The average intensity of a portion of the liver 402 is also calculated. For example, a portion of the liver 402 (e.g., with a width of 20 to 50 pixels) at the same or similar depth as a portion of the hepatorenal interface 406. In some examples, multiple portions of the liver 402 at the same or similar depth as multiple portions of the hepatorenal interface 406. The average intensity of the hepatorenal interface 406 (or one or more portions thereof) is compared to the average intensity of a portion (or multiple portions thereof) of the kidney 402 to determine whether the imaging plane is suitable. In some cases, the imaging plane is inappropriate if the mean intensity of the hepatorenal interface 406 is below a certain percentage of the mean intensity of the liver 402 and / or above a certain percentage of the mean intensity of the liver 402. For example, the imaging plane is appropriate if the mean intensity of the hepatorenal interface 406 is greater than or equal to 1.5 * mean intensity of the liver 402, but less than or equal to 1.3 * mean intensity of the liver 402.

[0042]

[0052] In addition to or instead of this, the mean intensity of the hepatorenal interface 406 is compared to the maximum brightness of images 401, 403 to determine whether the imaging plane is appropriate. For example, if the mean intensity of the hepatorenal interface 406 is greater than a certain percentage of the maximum brightness (e.g., 0.7, 0.8), the hepatorenal interface 406 is too bright and the kidney 404 is too dark. In some cases, the mean intensity of the hepatorenal interface 406 is compared to both the maximum brightness of the image and the mean intensity of the liver 402 to determine the appropriateness of the imaging plane.

[0043]

[0053] In some examples, the display 400 provides an indicator regarding whether the average intensity of the pixels in the hepatic interface 406 is appropriate as text, in a manner similar to the angle indicator 424. In some examples, a graphical overlay includes a curve fitted to the hepatic interface 406, and this curve changes color when the average intensity is within an appropriate range.

[0044]

[0054] After an image is acquired, in some examples, the ultrasound imaging system analyzes the image to confirm that the image quality is suitable for obtaining an HRI measurement and / or to guide the user to select an appropriate ROI in the image. In some examples, the ultrasound imaging system subdivides the acquired image into multiple parts. One or more parameters are extracted from each part. In some examples, if the extracted parameters fall within a certain range, the image is determined to have suitable image quality for obtaining an HRI measurement. In some examples, parameters from adjacent parts are compared. In some examples, if two adjacent parts have parameters with sufficiently similar values, the image is determined to have suitable image quality for obtaining an HRI measurement. If an image is deemed not to have suitable image quality, the ultrasound imaging system prompts the user to acquire another image (e.g., via a text warning on display 138). The ultrasound imaging system then returns to acquisition guidance, as described with reference to Figures 4A and 4B.

[0045]

[0055] Figure 5 shows an exemplary image including a portion of the liver and kidney subdivided into multiple parts according to the principles of this disclosure. Image 500 includes a portion of the liver 502, a portion of the kidney 504, and a portion of the hepatorenal interface 506. As described, one or more processors, such as image processor 136, segment the image 500 and / or fit a curve 510 to the hepatorenal interface 506. Based at least partially on this segmentation and / or curve 510, one or more processors determine the upper boundary 526 and the lower boundary 528 of the kidney 504. The region between the upper boundary 526 and the lower boundary 528 of the kidney 504 is divided into multiple subbands (e.g., depth bands) 530. In some examples, the width of the subbands is approximately 1 cm to 1.5 cm. One or more parameters of pixels within each subband (e.g., intensity distribution, mean intensity, standard deviation of intensity, signal-to-noise ratio, etc.) are determined. In some cases, if one or more parameters of the subbands are within an acceptable range, image 500 is determined to have sufficient image quality to obtain an HRI measurement. In some cases, the parameters of a subband are compared to the parameters of one or more adjacent subbands. In some cases, if two adjacent subbands have sufficiently similar parameters (e.g., within 10% and 20%), the image is determined to have sufficient image quality to obtain an HRI measurement.

[0046]

[0056] In some examples, the ultrasound imaging system divides subbands into sublengths and extracts pixel parameters from at least one sublength from each subband. Figure 6 shows an exemplary image including a portion of the liver and kidney subdivided into multiple parts according to the principles of the present disclosure. Image 600 includes a portion of the liver 602, a portion of the kidney 604, and a portion of the hepatorenal interface 606. As described, one or more processors, such as image processor 136, segment the image 600 and / or fit a curve 610 to the hepatorenal interface 606. Based at least partially on this segmentation and / or curve 610, one or more processors divide a portion of the image 600 from the upper boundary of the kidney 604 to the lower boundary of the kidney 604 into sublengths. The dashed line 636 defines the first sublength 638 on the liver 602 side of the hepatorenal interface 606 and the sublength 640 on the kidney 604 side of the hepatorenal interface 606.

[0047]

[0057] In some examples, parameters are extracted from sublengths 638 and 640 for each subband (not shown in Figure 6; see Figure 5). That is, not all pixels contained within the entire subband are necessarily used for parameter extraction; rather, only pixels contained within the sublengths are used. In some examples, two parameter values ​​are extracted for each subband. For example, a value for one parameter is extracted for sublength 638 of a subband, and another value for that parameter is extracted for sublength 640 of the same subband. In some examples where parameters of adjacent subbands are compared, the parameter values ​​for sublength 638 are compared with each other, and the parameter values ​​for sublength 640 are compared with each other.

[0048]

[0058] In some examples, the width of the second sublength 640 is at least partially based on the width of the renal cortex 642 of the kidney 604. In some examples, the widths of the first and second sublengths 638, 640 are at least partially based on the width of the subbands so that there are enough pixels in each sublength of each subband in order to extract parameters from each sublength of each subband. For example, a portion of the image within a certain sublength of a certain subband is approximately 1 cm to 1.5 cm × 1 cm to 1.5 cm.

[0049]

[0059] Figure 7 shows exemplary plots of parameter values ​​extracted from images according to the principles of this disclosure. Plots 700 and 705 show the distribution of pixel intensity in multiple different subbands of an image, such as image 500 and / or image 600. In plot 700, each curve represents the pixel intensity distribution for different subbands (e.g., subband 530) with subwidths (e.g., subwidth 638) associated with the liver. In plot 705, each curve represents the pixel intensity distribution for different subbands (e.g., subband 530) with subwidths (e.g., subwidth 640) associated with the kidney. The fifth band is the subband closest to the bottom of the kidney (e.g., adjacent to the line to the lower boundary 528), and the first subband is the subband closest to the top of the kidney (e.g., adjacent to the line to the upper boundary 526).

[0050]

[0060] In both plots 700 and 705, the curves for each subband are approximately Gaussian in distribution, with the peak gradually shifting due to attenuation as depth increases. However, there are no significant changes in distribution width or peak shift between adjacent subbands. Thus, the extracted parameters for each subband suggest that this image has suitable image quality for obtaining HRI measurements. In some cases, the cross-correlation coefficient (CCC) is calculated for two adjacent curves. The CCC is compared to a threshold to determine whether adjacent subbands are sufficiently similar. For example, the maximum value of the CCC is 1, and if the CCC is greater than or equal to 0.70, these subbands are considered sufficiently similar.

[0051]

[0061] If one or more curves exhibit a non-Gaussian distribution and a significant shift occurs between the peaks of low CCCs and / or adjacent subbands, it suggests that the image does not have the image quality suitable for HRI measurement. For example, a significant shift in peak intensity suggests the presence of blood vessels or cysts in the subbands. In other cases, a non-Gaussian distribution suggests image artifacts that may affect the HRI measurement.

[0052]

[0062] The example shown in Figure 7 illustrates the pixel intensity distribution, but other parameters may be extracted from subbands and / or sub-widths of subbands in other examples. For example, SNR and / or average pixel intensity are calculated. In some examples, rather than calculating the subband parameters relative to each other, the average of the extracted parameters is calculated to determine whether the image has adequate quality. In some examples, a weighted average is used. In some examples, the subband closest to the base of the kidney and the subband closest to the apex of the kidney are ignored and / or given a smaller weight because these bands are less likely to be used to obtain HRI measurements. If, based on the extracted parameters, it is determined that the image does not have adequate quality, the ultrasound imaging system prompts the user to acquire a new image.

[0053]

[0063] In some cases, parameters extracted from subbands are used to individually evaluate each subband in terms of its suitability for obtaining HRI measurements. For example, if the SNR of a particular subband does not meet a threshold, the ultrasound imaging system provides the user with an instruction that that particular subband should not be used to select an ROI for HRI measurement, rather than prompting the user to acquire a new image.

[0054]

[0064] If the image quality is deemed suitable for obtaining HRI measurements, the ultrasound imaging system provides the user with guidance, such as visual cues, for selecting a suitable ROI for calculating the HRI.

[0055]

[0065] Referring again to Figure 5, in some examples, a display such as display 138 provides a graphic overlay corresponding to curves 510, straight lines 526, 528, and / or subbands 530. Optionally, the display provides a graphic overlay corresponding to subwidths 638, 630. In some examples, the display information for the graphic overlay is provided by one or more processors, such as graphics processor 140 and / or image processor 136. By providing subbands 530 on the display, the user is guided to appropriately select ROIs at the same depth. By providing curves 510, the user is guided to appropriately select one ROI in the liver 502, such as exemplary liver ROI 532, and one ROI in the kidney 504, such as exemplary ROI 534. By providing subwidths 640, the user is guided to appropriately position ROI 534 in the renal cortex rather than other parts of the kidney 504. By providing a sub-width of 638, the user is guided to select the portion of the liver 502 that is close to the kidney 504.

[0056]

[0066] As described with reference to Figure 7, optionally, in some examples, the display provides a graphical overlay (not shown) indicating that a certain subband should not be used to locate ROI 532, 534. Examples include, but are not limited to, hash marks, “graying out” the subbands, and / or “Not for Use” text above the subbands.

[0057]

[0067] Optionally, in some examples, text and / or other cues are provided on the display to the user. For example, if the user places ROI 532, 534 outside of different subbands and / or subwidths, a textual warning appears. In other examples, if one of ROI 532, 534 is placed outside of different subbands and / or subwidths, one or both of ROI 532, 534 changes color. In other examples, the system does not allow the user to place ROIs outside of different subbands and / or appropriate subwidths. In some examples, the user selects whether subbands, subwidths, and / or other visual cues for selecting ROIs are provided on the display by providing input via a user interface, such as user interface 124.

[0058]

[0068] Figure 8 shows an exemplary region of interest according to the principles of this disclosure. Image 800 is the ROI of the liver, which is obtained from images such as Image 500 and / or Image 600. Image 805 is the ROI of the kidney, which is obtained from images such as Image 500 and / or Image 600. In some examples, Image 800 corresponds to ROI 532 and Image 805 corresponds to ROI 534. The HRI measurement is calculated based at least in part on Images 800 and Image 805. Typically, the HRI is determined by calculating the mean intensity of Image 800 and then calculating the mean intensity of Image 805. The HRI is obtained by dividing the mean intensity of Image 800 by the mean intensity of Image 805.

[0059]

[0069] Therefore, as disclosed herein, in the first stage, the user is guided to acquire an image on a suitable imaging plane by providing guidance relating to, for example, the angle of the hepatorenal interface within a centrally located bounding box and / or the position of the hepatorenal interface. Optionally, additional guidance is provided based on the average intensity of the pixels of the hepatorenal interface. In the second stage, the image acquired on the suitable imaging plane during the first stage is evaluated for image quality. In some examples, a portion of the image is subdivided into subbands, and this evaluation may be based on an analysis of at least some of the pixels of the individual subbands. If the image quality is not satisfactory, the imaging system returns to the first stage. However, after it is determined that the image quality is satisfactory, subbands and / or other visual guidance (e.g., sub-widths) are provided to help the user appropriately position the ROI on the image. After the ROI is positioned, the HRI is calculated.

[0060]

[0070] Figure 9A is a flowchart of the method according to the principles of the present disclosure. Flowchart 900A provides a technique for providing a user with guidance for acquiring an image on an imaging plane suitable for obtaining HRI measurements. In some examples, the method shown in Figure 9A is performed by an ultrasound imaging system, such as ultrasound imaging system 100. For example, one or more processors of ultrasound imaging system 100, such as image processor 136 and graphics processor 140, execute one or more instructions to perform some or all of the method shown in Figure 9A. In some examples, these instructions are stored in a non-temporary computer-readable medium, such as local memory 142.

[0061]

[0071] As shown in block 902, one or more processors receive the image. One or more processors segment the image to extract the liver region, the kidney region, and the hepatorenal interface, as shown in block 904. One or more processors fit a curve to the hepatorenal interface, as shown in block 906. After the curve has been fitted, the midpoints of the curve are calculated to find the positions of the anchor points, as shown in block 908. Based at least partially on the curve and the anchor points, one or more processors determine the tangents to the curve at the anchor points, as shown in block 910. The horizontal lines at the anchor points are also determined by one or more processors, as shown in block 912.

[0062]

[0072] As shown in block 914, one or more processors calculate the angle between the tangent and the horizontal line. In some examples, the suitability of the image is at least partially based on a comparison of this angle with a threshold (e.g., 30 degrees).

[0063]

[0073] As shown by block 916, the image currently being acquired is displayed (for example, on display 138). Visual cues are also displayed as a graphical overlay on the image, as shown by block 918. In some examples, the visual cues are based at least partially on the tangent and the angle between the tangent and the horizontal line. In some examples, the visual cues include anchor points, tangents, and / or horizontal lines. In some examples, an angle indicator, such as indicator 424, is also displayed. In some examples, a bounding box, such as bounding box 418, is displayed in the central part of the displayed image. This helps the user in acquiring an image with the appropriate imaging plane to obtain HRI measurements. Of course, the operations performed in blocks 902-918 are performed continuously and / or iteratively as the user moves the ultrasound probe and new images are acquired by the ultrasound imaging system.

[0064]

[0074] Figure 9B is a flowchart of the method according to the principles of this disclosure. The method shown in flowchart 9B provides a technique for guiding the user in selecting an appropriate ROI and determining the suitability of an image for HRI measurement. In some examples, the method shown in Figure 9B is performed by an ultrasound imaging system, such as ultrasound imaging system 100. For example, one or more processors of ultrasound imaging system 100, such as image processor 136 and graphics processor 140, execute one or more instructions to perform some or all of the method shown in Figure 9A. In some examples, these instructions are stored in a non-temporary computer-readable medium, such as local memory 142. In some examples, the method shown in Figure 9B is performed after the method shown in Figure 9A has been performed.

[0065]

[0075] As shown by block 920, one or more processors determine the upper and lower boundaries of the kidney region in the image. One or more processors divide the region between these boundaries into several subbands, as shown by block 922. In some examples, one or more processors extract parameters from each of these subbands or from at least some of the pixels of at least some of these subbands, as shown by block 924. In some examples, one or more processors further divide the subbands into sub-widths such as sub-widths 638 and 640, and parameters are extracted from the sub-widths of these subbands. One or more processors determine whether the image has adequate image quality, at least partially based on these parameters, as shown by block 926. In some examples, whether the image has adequate image quality is determined at least partially based on comparing the parameters of adjacent subbands with each other. In some examples, whether the image has adequate image quality is determined at least partially based on comparing one or more parameters with one or more thresholds.

[0066]

[0076] Subbands and / or subwidths are displayed as graphical overlays on the image, as shown by block 928. The subbands and / or subwidths provided on the display guide the user to position the ROIs in appropriate regions of the liver and kidneys. The graphical overlays further guide the user to position the ROIs at the same depth. One or more processors receive user input indicating the ROIs (e.g., via a user interface such as user interface 124), as shown by blocks 930 and 932. Based at least partially on the pixels located in the ROIs, one or more processors calculate the HRI, as shown by block 934. In some examples, the HRI is provided as text on the display along with the image.

[0067]

[0077] Figure 10 is a block diagram illustrating an exemplary processor 1000 according to the principles of this disclosure. Processor 1000 is used to implement one or more processors and / or controllers described herein, such as the image processor 136 shown in Figure 1 and / or any other processor or controller shown in Figure 1. Processor 1000 may be any suitable type of processor, including, but is not limited to, a microprocessor, a microcontroller, a digital signal processor (DSP), a field-programmable gate array (FPGA) programmed to form a processor, a graphical processing unit (GPU), an application-specific integrated circuit (ASIC) designed to form a processor, or a combination thereof.

[0068]

[0078] The processor 1000 includes one or more cores 1002. Each core 1002 includes one or more arithmetic logic units (ALUs) 1004. In some embodiments, the core 1002 includes, in addition to or instead of, the ALUs 1004, a floating-point logic unit (FPLU) 1006 and / or a digital signal processing unit (DSPU) 1008.

[0069]

[0079] The processor 1000 includes one or more registers 1012 that are communicatively coupled to the core 1002. The registers 1012 are implemented using dedicated logic gate circuits (e.g., flip-flops) and / or memory technology. In some embodiments, the registers 1012 are implemented using static memory. The registers provide data, instructions, and addresses to the core 1002.

[0070]

[0080] In some embodiments, the processor 1000 includes one or more levels of cache memory 1010 that are communicatively coupled to the core 1002. The cache memory 1010 provides computer-readable instructions to the core 1002 for execution. The cache memory 1010 provides data for processing by the core 1002. In some embodiments, the computer-readable instructions are provided to the cache memory 1010 by local memory, such as local memory attached to an external bus 1116. The cache memory 1010 is implemented using any suitable type of cache memory, such as metal oxide semiconductor (MOS) memory, such as static random access memory (SRAM), dynamic random access memory (DRAM), and / or any other suitable memory technology.

[0071]

[0081] The processor 1000 includes a controller 1014, which controls inputs to the processor 1000 from other processors and / or components included in the system (e.g., the control panel 152 and scan converter 130 shown in Figure 1), and / or outputs from the processor 1000 to other processors and / or components included in the system (e.g., the display 138 and volume renderer 134 shown in Figure 1). The controller 1014 controls the data paths in the ALU 1004, FPLU 1006, and / or DSPU 1008. The controller 1014 is implemented as one or more state machines, data paths, and / or dedicated control logic. The gates of the controller 1014 are implemented as standalone gates, FPGAs, ASICs, or any other suitable technology.

[0072]

[0082] Register 1012 and cache memory 1010 communicate with controller 1014 and core 1102 via internal connections 1020A, 1020B, 1020C, and 1020D. These internal connections are implemented as buses, multiplexers, crossbar switches, and / or any other suitable connection technology.

[0073]

[0083] Inputs and outputs for the processor 1000 are provided via bus 1016, which includes one or more conductive lines. Bus 1016 is communicably connected to one or more components of the processor 1000, such as controller 1014, cache memory 1010, and / or registers 1012. Bus 1016 is coupled to one or more components of the system, such as the previously mentioned display 138 and control panel 152.

[0074]

[0084] Bus 1016 is coupled to one or more external memories. The external memory includes read-only memory (ROM) 1032. ROM 1032 is a mask ROM, an electronically programmable read-only memory (EPROM), or any other suitable technology. The external memory includes random access memory (RAM) 1033. RAM 1033 is a static RAM, a battery-backed static RAM, a dynamic RAM (DRAM), or any other suitable technology. The external memory includes electrically erasable programmable read-only memory (EEPROM) 1035. The external memory includes flash memory 1034. The external memory includes a magnetic storage device, such as a disk 1036. In some embodiments, the external memory is included in a system such as the ultrasound imaging system 100 shown in Figure 1, for example, a local memory 142.

[0075]

[0085] The systems, methods, and apparatus disclosed herein provide scanning or imaging plane recognition techniques and / or ultrasound image quality control techniques that, in some examples, can be used in imaging of the liver in general where HRI measurements are desired to reduce the workload of busy ultrasound users. In some examples, these systems, methods, and apparatus are implemented in ultrasound imaging systems that provide raw data / RF signals and / or DICOM images. In some examples, these systems, methods, and apparatus are included as components of a computer-aided diagnostic (CAD) system to help physicians performing hepatic ultrasound examinations determine key parameter measurements and reporting.

[0076]

[0086] Although described with reference to liver imaging, the techniques described herein can be applied to previously acquired images, such as DICOM images stored in a picture archiving and communication system (PACS). For example, previously acquired images can be segmented and analyzed as described with reference to Figures 2-4, and if the angles are deemed appropriate, previously acquired images can be analyzed as described with reference to Figures 5-7. If previously acquired images are suitable for obtaining HRI measurements, the user is guided to appropriately select ROIs, and HRI measurements are calculated as described with reference to Figures 5 and 8.

[0077]

[0087] In various embodiments in which components, systems, and / or methods are implemented using programmable devices such as computer-based systems or programmable logic, it should be understood that the above-described systems and methods can be implemented using any of the various known or future-developed programming languages ​​such as C, C++, C#, Java, and Python. Therefore, various storage media, such as magnetic computer disks, optical disks, and electronic memory, can be provided that can contain information that can instruct a device, such as a computer, to implement the above-described systems and / or methods. After a suitable device accesses the information and programs contained on the storage medium, the storage medium can provide the information and programs to the device, thereby enabling the device to perform the functions of the systems and / or methods described herein. For example, if a computer disk containing appropriate materials such as source files, object files, and executable files is provided to a computer, the computer can receive that information, configure itself appropriately, and perform the functions of the various systems and methods outlined in the above-described drawings and flowcharts for performing various functions. That is, the computer can receive various parts of information regarding different elements of the above-described systems and / or methods from the disk, implement individual systems and / or methods, and coordinate the functions of the individual systems and / or methods described above.

[0078]

[0088] It should be noted that, according to this disclosure, various methods and devices described herein can be implemented as hardware, software, and firmware. Furthermore, various methods and parameters are included only by example and without any limitation. By referring to this disclosure, those skilled in the art can implement these teachings while remaining within the scope of the invention when determining their own techniques and the equipment required that would affect these techniques. One or more functions of the processors described herein can be incorporated into fewer or a single processing unit (e.g., a CPU) and can be implemented using application-specific integrated circuits (ASICs) or using general-purpose processing circuits programmed in response to executable instructions for performing the functions described herein. Furthermore, the system also includes one or more programs used in conjunction with conventional imaging systems to provide the features and advantages of the system. Certain additional advantages and features of the disclosure will be apparent to those skilled in the art by examining this disclosure and can be experienced by those adopting the novel systems and methods of the disclosure. Another advantage of this system and method is that conventional medical imaging systems can be easily upgraded to incorporate the features and advantages of this system, device, and method.

[0079]

[0089] Of course, it should be understood that, according to this system, device, and method, any of the examples, embodiments, or processes described herein may be combined with or separated from one or more other examples, embodiments, and / or processes, and / or may be performed between separate devices or parts of devices.

[0080]

[0090] Finally, the above discussion is intended to be merely illustrative of the system and should not be construed as limiting the appended claims to any particular embodiment or group of embodiments. Thus, although the system has been described in certain details with reference to exemplary embodiments, those skilled in the art will understand that many modifications and alternative embodiments can be devised without departing from the broader, intended spirit and scope of the system as described in the following claims. Accordingly, this specification and drawings should be considered exemplary and are not intended to limit the scope of the appended claims.

Claims

1. An ultrasound imaging system that provides user guidance for acquiring images suitable for measuring the hepatic-renal index, wherein the ultrasound imaging system is A non-temporary computer-readable medium encoded with instructions, A non-temporary computer-readable medium and at least one processor that communicates with the non-temporary computer-readable medium and executes the instruction, wherein when the instruction is executed, the at least one processor, The liver region, kidney region, and hepatorenal interface are segmented from the image. The curve is fitted to the aforementioned liver-kidney interface, The anchor point at the midpoint of the aforementioned curve is calculated. Determine the tangent line between the anchor point and the curve, Determine the horizontal line at the aforementioned midpoint, The angle between the tangent line and the horizontal line is calculated. To generate a visual cue for display that is at least partially based on the tangent line and the angle between the tangent line and the horizontal line, At least one processor, A display that shows the aforementioned image and the visual cue as a graphical overlay on the aforementioned image, An ultrasound imaging system equipped with [specific features / equipment].

2. The ultrasonic imaging system according to claim 1, further comprising the instruction causing the at least one processor to calculate the average intensity of a plurality of pixels of the hepatic interface.

3. The ultrasonic imaging system according to claim 1, wherein the visual cue includes an indicator indicating the angle, and the display shows the indicator.

4. The ultrasonic imaging system according to claim 3, wherein the indicator provides a qualitative indicator of the angle, and the qualitative indicator is at least partially based on a comparison of the angle with a threshold.

5. The instruction further provides the at least one processor with, Determine the upper and lower boundaries of the aforementioned renal region. The region of the image between the upper boundary and the lower boundary is divided into a plurality of subbands. Multiple parameters are extracted from corresponding subbands among the aforementioned multiple subbands. The determination of whether the image has appropriate image quality is made based at least partially on the aforementioned multiple parameters. The ultrasonic imaging system according to claim 1.

6. The ultrasound imaging system according to claim 5, wherein the individual parameters of the plurality of parameters are extracted from a portion of the pixels of the corresponding subbands of the plurality of subbands.

7. The ultrasonic imaging system according to claim 5, wherein the image is determined to have appropriate image quality based on a comparison of the plurality of parameters and a threshold.

8. The ultrasound imaging system according to claim 5, wherein the image is determined to have adequate image quality based at least in part on a comparison between one parameter of the plurality of parameters of one subband among the plurality of subbands and another parameter of the plurality of parameters of an adjacent subband among the plurality of subbands.

9. The ultrasound imaging system according to claim 5, wherein the instruction further causes the at least one processor to divide the individual subbands of the plurality of subbands into at least two subwidths, the first subwidth including at least a portion of the liver region and the second subwidth including at least a portion of the kidney region.

10. The instruction further provides to at least one processor: Determine the upper and lower boundaries of the aforementioned renal region. The region of the image between the upper boundary and the lower boundary is divided into a plurality of subbands. To generate display information for the aforementioned multiple subbands, The display shows the plurality of subbands. The ultrasonic imaging system according to claim 1.

11. The ultrasound imaging system according to claim 10, further comprising a user interface for receiving user input including a first region of interest in the liver region and a second region of interest in the kidney region.

12. A method for operating an ultrasound imaging system that provides user guidance for acquiring images suitable for measuring the hepatic-renal index, The steps include: at least one processor of the ultrasound imaging system receiving an image; The processor performs the steps of segmenting the liver region, the kidney region, and the hepatorenal interface from the image, The processor performs the step of fitting a curve to the hepatic interface, The processor performs the steps of calculating the anchor point at the midpoint of the curve, The processor performs the steps of determining the tangent line to the curve at the anchor point, The processor performs the steps of determining the horizontal line at the midpoint, The processor performs the steps of calculating the angle between the tangent line and the horizontal line, The processor performs the step of displaying the image on the display of the ultrasonic imaging system, The processor displays on the display a visual cue, at least partially based on the tangent and the angle between the tangent and the horizontal line, as a graphical overlay on the image. A method for operating an ultrasonic imaging system, comprising the characteristics of an ultrasonic imaging system.

13. The method for operating an ultrasonic imaging system according to claim 12, wherein the visual cue further includes an indicator of the angle.

14. The method for operating an ultrasonic imaging system according to claim 12, wherein the visual cue includes at least one of the tangent line or the horizontal line, and the processor further comprises the step of changing the color of at least one of the tangent line or the horizontal line based on a comparison of the angle and a threshold.

15. The method for operating an ultrasonic imaging system according to claim 12, further comprising the step of the processor displaying a bounding box on the display as a graphical overlay in the central portion of the image.

16. The processor comprises the steps of determining the upper boundary and the lower boundary of the kidney region, The processor divides the region of the image between the upper boundary and the lower boundary into a plurality of subbands, A method for operating an ultrasonic imaging system according to claim 12, further comprising the above.

17. The processor comprises the steps of extracting a plurality of parameters from a corresponding subband among the plurality of subbands, The processor determines whether the image has appropriate image quality based at least partially on the plurality of parameters, A method for operating an ultrasonic imaging system according to claim 16, further comprising the above.

18. The method for operating an ultrasonic imaging system according to claim 17, wherein the image is determined to have appropriate image quality based at least partially on a comparison between one parameter of the plurality of parameters of one of the plurality of subbands and another parameter of the plurality of parameters of an adjacent subband of the plurality of subbands.

19. The method for operating an ultrasonic imaging system according to claim 16, further comprising the step of the processor displaying the plurality of subbands on the display as a graphical overlay on the image.

20. The processor receives a first user input indicating a first region of interest in one of the plurality of subbands in the liver region, The processor receives a second user input indicating a second region of interest in one of the multiple subbands in the renal region, The processor calculates the hepatorenal index based at least partially on the first region of interest and the second region of interest, A method for operating an ultrasonic imaging system according to claim 19, further comprising the above.

Images