Methods for performing automated measurements over multiple cardiac cycles

Abstract

The present invention is entitled "A Method for Performing Automated Measurements Across Multiple Cardiac Cycles". An automated measurement system for ultrasound and / or echocardiographic imaging systems enhances the reproducibility of measurement results and adapts to formation shifts in the image measurements by combining measurements across multiple cardiac cycles / multiple echocardiographic images. This automated system provides these benefits by initially selecting cardiac images / cycles from which effective measurements can be obtained within constraints defined by the system. In the case of these selected cycles, the automated system then combines measurements from the selected cycles into a global measurement of one or more desired parameters of the combined cycle. The result of the deviation of the combined measurements, optionally along with a display icon representing the deviation from the illustrated cycle image, is then presented to the operator, in combination with an image or cycle representation of the cycle that best approximates the global measurement result.

Description

Technical Field

[0001] This disclosure relates generally to medical diagnostic equipment, and more specifically to ultrasound and / or echocardiography equipment. Background Technology

[0002] Echocardiography (sometimes called diagnostic echocardiography) is a well-known medical test that uses high-frequency sound waves (ultrasound) to generate images of a patient's heart. Echocardiography uses sound waves to produce images of the heart's chambers, valves, walls, and blood vessels (aorta, arteries, veins). During echocardiography, a probe, called a transducer, is passed through the patient's chest and used to generate sound waves that bounce off the heart structures and “echo” back to the probe. The detected “echoes” are converted into digital images that can be viewed on a computer monitor.

[0003] To detect these conditions and form the resulting images for display, the most common modes of diagnostic ultrasound imaging include B-mode and M-mode (for images of internal structures and physical structures), spectral Doppler, and color flow (the latter two primarily used for imaging flow characteristics, such as in blood vessels), as disclosed in U.S. Patent No. 8,469,887 entitled “Method and Apparatus For Flow Parameter Imaging,” the entire contents of which are expressly incorporated herein by reference for all purposes. In this application, all references to echocardiography and / or echocardiographic images refer to the procedures and / or images obtained using any of these imaging types or modes (e.g., B-mode / M-mode / spectral Doppler / color Doppler, etc.).

[0004] Color flow mode is typically used to detect blood flow velocity toward / away from the transducer, and it essentially utilizes the same technique as that used in spectral Doppler mode. While spectral Doppler mode displays the velocity versus time relationship of a single selected sample volume, color flow mode simultaneously displays hundreds of adjacent sample volumes, all laid out on the B-mode image and color-coded to represent the velocity of each sample volume.

[0005] Measuring blood flow in the heart and blood vessels using the Doppler effect is well-known. The phase shift of backscattered ultrasound waves can be used to measure the velocity of the backscattered particles from tissue or blood. Different colors can be used to display the Doppler shift to indicate the velocity and direction of the flow. Alternatively, in power Doppler imaging, the power contained in the returned Doppler signal is displayed.

[0006] B-mode ultrasound images consist of multiple image scan lines. The brightness of a pixel is based on the intensity of the echo returned from the scanned biological tissue. The outputs of the receiving beamformer channels are coherently summed to form the corresponding pixel intensity value for each sample volume within the object region or volume of interest. These pixel intensity values ​​are logarithmically compressed, scan-converted, and then displayed as a B-mode image of the scanned anatomical structure.

[0007] Furthermore, ultrasound scanners used for detecting blood flow based on the Doppler effect are well known. Such systems operate by actuating an array of ultrasound transducers to transmit ultrasound waves into an object and to receive the echoes backscattered from the object. For the same scan line and focal point, the sequence of transmitting waves and receiving echo signals is repeated several times. The set of echo signals generated from the same acquisition is called a lumped array. Since the lumped array consists of beams with the same beamforming, the only difference between the beams is information about the position of the scatterer. Changes in the position of the scatterer are translated into a phase shift in the received signal. This phase shift is further translated into the velocity of the blood flow. The blood velocity is calculated by measuring the phase shift from initiation to initiation at a specific distance gate.

[0008] Color flow images are generated by overlaying a color image with the velocity of moving material (such as blood) onto a black-and-white anatomical B-mode image. Typically, a color flow pattern displays hundreds of adjacent sample volumes simultaneously overlaid on a B-mode image, each sample volume being color-coded to represent the velocity of moving material within that sample volume at the time of inquiry.

[0009] In other ultrasound scanners, the Doppler waveform of pulsed or continuous waves is also calculated and displayed in real time as a grayscale spectrum representing the velocity versus time relationship, where grayscale intensity (or color) is modulated by spectral power. The data for each spectral line includes multiple frequency data bins at different frequency intervals, with the spectral power data in each bin of the corresponding spectral line displayed as corresponding pixels in the corresponding pixel column on the monitor. Each spectral line represents an instantaneous measurement of blood flow.

[0010] Using any of these imaging modalities, echocardiography is used to identify a variety of different cardiac conditions in a patient and to provide medical personnel with information about the structure and function of the heart. For example, using echocardiography, medical personnel can identify and / or obtain measurements / measurements related to one or more of the following: a) the size and shape of the heart; b) the size, thickness, and movement of the heart walls; c) the movement of the heart; d) the strength of the heart's pumping; e) whether the heart valves are functioning properly; f) whether blood is leaking backward through the heart valves (backflow); g) whether the heart valves are too narrow (stenosis); h) whether there are tumors or infectious growths around the heart valves; i) problems with the pericardium (the lining of the heart); j) problems with the great vessels entering and leaving the heart; k) blood clots in the heart chambers; and l) abnormal openings between the heart chambers.

[0011] To identify one or more of these problems in the images received by the echocardiogram transducer, the operator will preview the images and attempt to locate any problems shown in the presented images. As images for each cardiac cycle (heartbeat) are acquired, the operator will review each image from each cycle to make this determination. In most cases, the operator examines the images from each cycle and selects the one that best illustrates the heart's structures to make a determination based on the operator's experience.

[0012] When operator opinion and experience are crucial in selecting the cycle used to determine a patient's condition, significant variations in measurement results arise due to the choice of cycle for measurement. Therefore, there are significant issues regarding the reproducibility of echocardiographic measurements using a manual cycle selection process.

[0013] To address the lack of reproducibility in echocardiographic measurements, automated measurement systems have been developed. These systems automatically measure images associated with each cycle to normalize or score the images regarding the degree of normality or abnormality present within each image. For example, an automated system could apply simple normal or abnormal scores to images from a cardiac cycle to classify them as normal or abnormal based on preset image parameters stored and utilized by the automated system (such as the system employed in U.S. Patent Application Publication No. US2020 / 0185084, the entire text of which is expressly incorporated herein by reference for all purposes). An operator could then examine images scored as abnormal to more quickly assess problems with those images, rather than having to evaluate images scored as normal by the automated system.

[0014] However, even with automated measurement systems, the reproducibility of results from echocardiographic images remains problematic. In many cases, significant changes frequently occur in the images due to patient movement during image acquisition, such as due to the patient's breathing, probe movement, or different reflections from the imaging tissue. Since motion during the cardiac cycle causes features of interest to shift out of the image plane, this movement inevitably leads the automated measurement system to classify or score the image for that cycle as abnormal. Therefore, because the abnormality score assessed by the automated measurement system still requires the operator to examine the image, even if the abnormality is solely due to movement from the patient's breathing rather than any actual abnormality being imaged in the heart.

[0015] Therefore, it is desirable to develop a measurement system for evaluating and classifying echocardiographic images in a manner that provides enhanced reproducibility of measurement results along with the ability to adapt the images to movement across multiple cardiac cycles. Summary of the Invention

[0016] According to one aspect of an exemplary embodiment of the invention, an automated measurement system for an ultrasound and / or echocardiographic imaging system is provided, which enhances the reproducibility of measurement results and adapts to formation shifts in image measurements by combining measurements across multiple cardiac cycles / multiple echocardiographic images. Echocardiographic image data may include, but is not limited to, Doppler image data, and echocardiographic images include, but are not limited to, images obtained by an ultrasound system operating in one or more modes among B-mode (2D / 3D) / M-mode / spectral Doppler / color mode Doppler. The automated system provides these benefits by initially selecting cardiac images / cycles within constraints defined by the automated system to obtain effective measurements. In the case of these selected cycles, the automated system then combines measurements from the selected cycles into a global measurement of one or more desired parameters of the combined cycle. The result of the deviation of the combined measurements, optionally along with a display icon representing the deviation from the illustrated cycle image, may be presented to the operator in combination with an image or cycle representation of the cycle that best approximates the global measurement result.

[0017] According to another aspect of an exemplary embodiment of the invention, the display icons may vary relative to each other in order to reflect the confidence level of the measurement represented by the various icons.

[0018] According to another aspect of an exemplary embodiment of the present invention, a method for performing automated echocardiographic measurements across multiple cardiac cycles is provided, the method comprising the steps of: providing an ultrasound imaging system including a control panel, a display, and a transducer, the control panel including a processing device configured to process ultrasound image data and an electronic storage device containing algorithms for access and utilization by the processing device, the display being operatively connected to the control panel, the transducer being operatively connected to the control panel to acquire ultrasound and echocardiographic image data and to transmit the ultrasound and echocardiographic image data to the control panel; acquiring a plurality of echocardiographic images over multiple cardiac cycles; selecting a subset of the echocardiographic images; calculating a global measurement from one or more measurement parameters of the subset of the echocardiographic images; and displaying the global measurement.

[0019] According to another aspect of an exemplary embodiment of the present invention, an ultrasound imaging system for performing automatic measurements from echocardiographic images acquired over multiple cardiac cycles is provided. The ultrasound imaging system includes a control panel, a display, and a transducer. The control panel includes a processing device configured to process ultrasound image data and an electronic storage device operatively connected to the processing device. The display is operatively connected to the control panel. The transducer is operatively connected to the control panel to acquire and transmit ultrasound image data to the control panel. The processing device is configured to employ one or more automatic measurement algorithms stored in the electronic storage device to select a subset of echocardiographic images from multiple echocardiographic images acquired by the transducer over multiple cardiac cycles based on one or more of image quality values, confidence metrics, or combinations thereof, and to calculate and display a global measurement of one or more parameters from the subset of echocardiographic images.

[0020] These and other exemplary aspects, features, and advantages of the invention will become apparent from the following description taken in conjunction with the accompanying drawings. Attached Figure Description

[0021] The accompanying drawings illustrate the currently conceived best mode for practicing the present invention.

[0022] In the attached diagram:

[0023] Figure 1 This is a schematic diagram of an echocardiographic imaging system according to an exemplary embodiment of the present invention.

[0024] Figure 2A and Figure 2B This is a diagram of echocardiographic images captured in spectral Doppler imaging mode over multiple cardiac cycles.

[0025] Figure 3A and Figure 3B It is a graphical representation of global measurements of multiple cardiac cycles obtained in spectral Doppler imaging mode, including measurement indicators for each cycle.

[0026] Figure 4A and Figure 4B It is an illustration of a global measurement of multiple cardiac cycles obtained in spectral Doppler imaging mode, including alternative implementations of measurement indicators for each cycle.

[0027] One or more specific implementations will be described below. To provide a concise description of these implementations, not all characteristics of the actual implementations may be described in this specification. It should be understood that, as in any engineering or design project, in the development of any such actual implementation, numerous implementation-specific decisions must be made to achieve the developer's specific objectives, such as complying with system-related and business-related constraints that may differ between implementations. Furthermore, it should be understood that such development efforts may be complex and time-consuming, but remain routine tasks of design, fabrication, and manufacturing for those skilled in the art who benefit from this disclosure.

[0028] When describing the elements of various embodiments of the invention, the articles “a,” “an,” “the,” and “the” are intended to refer to one or more of the elements present. The terms “comprising,” “including,” and “having” are intended to be inclusive and mean that additional elements may exist in addition to the listed elements. Furthermore, any numerical examples in the following discussion are intended to be non-limiting, and therefore the additional numerical values, ranges, and percentages are within the scope of the disclosed embodiments.

[0029] Figure 1 A high-level view is depicted of the components of an ultrasound and / or echocardiographic imaging system 10 capable of generating 2D or 3D images, including but not limited to images of selected areas of a patient obtained in spectral Doppler imaging mode, which may be suitable for specific implementations of the methods of the present invention. Specifically, the methods of the present invention may be implemented as storing one or more executable routines and / or algorithms on a memory or data storage component / database of the system 10 (such as present in a control panel 36) and / or stored by one or more application-specific integrated circuits (ASICs) of the system 10. The ultrasound system 10 shown includes a transducer array 14 having transducer elements 16 suitable for contact with a subject or patient 18 during a cardiac imaging procedure. It should be noted that the transducer array 14 may be configured as a bidirectional transducer and capable of emitting and receiving ultrasound waves into and from the subject or patient 18. In emission mode, the transducer array elements 16 convert electrical energy into ultrasound waves and emit them into the patient 18. In receiving mode, the transducer array element 16 converts the ultrasound energy (backscattered wave) received from the patient 18 into an electrical signal.

[0030] Each transducer element 16 is associated with a corresponding transducer circuit 20. That is, in the illustrated embodiment, each transducer element 16 in array 14 has a pulse generator 22, a transmit / receive switch 24, a preamplifier 26, a scan gain 34, and an analog-to-digital (A / D) converter 28. In other embodiments, this arrangement may be simplified or otherwise modified. For example, the components shown in circuit 20 may be located upstream or downstream of the depicted arrangement; however, each transducer element 16 generally still has the basic functions depicted.

[0031] In addition, various other imaging components 30 are provided to enable image formation using the ultrasound system 10. Specifically, illustrated examples of the ultrasound system 10 also include a beamformer 32, a control panel 36, a receiver 38, and a scan converter 40, which cooperate with the transducer circuitry 20 to generate images or a series / multiple echocardiographic images 42 (e.g., echocardiograms) that can be stored and / or displayed to an operator. Processing components 44 (e.g., microprocessors) and electronic storage devices or databases 46 of the system 10 (such as those present in the control panel 36) can be used to execute stored routines for processing acquired echocardiographic images to generate various measurements, other information, and / or motion frames, which, as described herein, can be displayed on the monitor 48 of the ultrasound system 10.

[0032] In the operating method, a transducer array or probe 14, including transducer element 16, is placed against the patient 18 and operated to acquire echocardiographic images 42. Typically, several cardiac cycles (i.e., 1-30 cycles) occur during each echocardiographic acquisition. Measurements obtained by the probe 14 across cardiac cycles during acquisition often exhibit some variability based on the movement of the probe 14, the movement of the patient 18 (i.e., breathing), or different reflections from there. To address this variability in measurement, the system 10 utilizes a processing unit or device 44 to calculate measurements across multiple cardiac cycles using an automated measurement algorithm contained within an electronic storage medium / database 46 and utilized by the processing unit 44, and subsequently visualizes these results to the user.

[0033] In a method for performing automated measurement determination on cardiac cycles occurring during ultrasound image acquisition, the first step is for processing device 44 to select the recorded cardiac cycles to be used for performing automated measurements. During the acquisition process, some images in certain cardiac cycles may not be suitable for calculating the desired measurements used for the acquisition for various reasons, including because the user switches between two views in a single acquisition, or because the patient's breathing causes features of interest to leave the image plane in certain cycles, etc. Examples of images 100, 102 acquired in spectral Doppler imaging mode and provided for measurements obtained for each of multiple cardiac cycles / images 42, and variations of these images 42 in... Figure 2A and Figure 2B As shown in the diagram. Due to variations in cardiac cycles caused by these and / or other reasons, in many cases, only a subset of echocardiographic images / cardiac cycles 42 may be used / provide accurate measurement information. Therefore, it is important that the processing device 44 be able to select only those echocardiographic images / cardiac cycles 42 for use in calculating desired measurements that provide accurate data or for measuring one or more determined parameters.

[0034] In one exemplary embodiment, the cycle selection step is performed by a view recognition algorithm employed by the processing device 44. When employing the view recognition algorithm, only those images 42 / cardiac cycles that produce stable classification results for image views with high confidence are included in the image set used for measurement calculations. For example, during this examination or selection process of the processing device 44, if a cycle / image 42 of interest for the patient 18's breathing is temporarily removed from the plane of image 42, the selection step enables the processing device 44 to automatically discard those cycles / images 42 from those used to determine the measurement result. The view recognition algorithm detects cardiac views, such as 2-chamber or 4-chamber views, obtained during each cardiac cycle to determine whether the view matches a desired view (e.g., a 2-chamber or 4-chamber view) for obtaining the desired measurement information. In a particular example, the desired view utilized by the view recognition algorithm may be a view directly centered at the apex of the left ventricle to prevent image shortages during measurement determination, wherein the view recognition algorithm also provides a confidence measure of the cardiac cycle / image 42 corresponding to each examined desired view for a particular cycle / image 42. When the processing device 44 determines, via a view recognition algorithm, that a view of a specific cardiac cycle corresponds to the desired view for measurement calculation, the processing device 44 may include a specific image for measurement calculation.

[0035] In another exemplary embodiment of the cycle selection step, the selection of the cardiac cycle to be used for measurement calculation is performed by a network that detects image quality. In this embodiment, cycle selection can be performed by any algorithm capable of determining image quality (e.g., an image quality confidence metric). A specific example would then be a neural network trained to classify images based on perceived quality, as determined by a clinical expert, to determine an image quality metric. For image quality determination, the network / image quality algorithm can utilize several different parameters, such as the brightness of the image alone or in combination with each other, the acoustic impedance of the image, the visibility of important structures, or others. In this embodiment, the network or image quality algorithm examines the images 42 for each cardiac cycle to determine the image quality of each cycle, with only the cycles containing the images with the lowest quality included for measurement determination.

[0036] In yet another exemplary embodiment, the selection step may be performed using a confidence metric for each cardiac cycle image 42, which provides an indication of the expected and / or “normal” measurement outcome for a particular cardiac cycle, such as a measurement variance confidence metric. Confidence metrics can take various forms and may originate from different sources. For example, a confidence metric may be extracted from or determined in relation to the output of the automated measurement algorithm itself. For example, a confidence metric may determine additional measurements for other cardiac cycles or, for example, relevant measurements for the same patient, based on a comparison of measurements for a particular cardiac cycle / image as determined by the automated measurement algorithm. A confidence metric may be based on the magnitude of any difference between the calculated measurement and the compared measurements, and may determine any images / cardiac cycles that fall outside an acceptable range around a predetermined value from the final measurement. Alternatively, as is the case with many deep learning algorithms, another algorithm in the processing step for measurement (such as a view recognition algorithm) may be used to determine a confidence metric / value for each cardiac cycle / image. Furthermore, particularly when the algorithm used is a neural network, other examples of algorithms that can be used to determine the confidence metric include, but are not limited to: a) a network that outputs the predicted output as a distribution of possible measurements; b) a network that outputs the prediction and separately outputs the measure of confidence; or c) a network used to process the same image multiple times, but with slightly varying parameters during each processing sequence, wherein the confidence metric is reached across those processing runs using the variance of the output / measurement.

[0037] In yet another exemplary embodiment, the selection step may be performed by the processing device 44 using a combination of one or more previously described embodiments of the selection step or process, such as by using a view to identify a confidence metric associated with an image quality metric and / or a measurement variance confidence metric.

[0038] After the cycle selection step is performed by processing device 44, the selected cardiac cycles / images 42 are employed in a second step to determine or calculate the desired parameters of each selected cardiac cycle in a single global measurement. This global measurement can be determined in a variety of acceptable ways, but in one exemplary embodiment, it is determined by averaging the selected cardiac cycles / measurement parameters for each cycle. This calculation can be performed as a simple mean / median or a weighted average of the cycle / cycle parameters, where the weighting comes from any method used in the cycle selection step, for example, where those cardiac cycles / images with higher image confidence and / or quality values ​​and / or higher confidence measures are given greater corresponding weight in the averaging.

[0039] Furthermore, a measure of global measurement validity or confidence of the average global measurement itself can be provided along with global measurements for all selected periods. In one exemplary embodiment, a global measurement validity or confidence value can be determined using one or both of a confidence measure extracted from each independent period or the variance between the individual measurements across the selected periods, each selected period may also be weighted by the confidence measures of the individual periods. Additionally, while a global measurement validity value can be displayed along with the global measurements in all cases, in some cases where the global measurement results are derived only from a single period that can be displayed to the user (e.g., 2D measurements), a median result or confidence measure can be used to determine the period / image 42 to be presented on display 48.

[0040] See now Figure 3A and Figure 3B After calculating global measurements and optionally global measurement validity from the cardiac cycles / images 42 selected in the first step of the method, the results of this analysis performed by the processing device 44 can be provided to the user on the display 48. In doing so, the processing device 44 determines the cycle image 42 selected in the first step that has the highest confidence metric and / or the highest image quality, which is selected by the processing device 44 in the selection step and used to determine the global measurement. This cycle image 42, along with calipers or indicators 50, is presented on the display 48 showing the measurement results across the individual cycles selected for determining the global measurement. In this way, in addition to showing the global measurement results (including, but not limited to, e.g., the mean / standard deviation across all selected cycles / images 42), and the cycle / image 42 best fitting this global measurement, all measurements of each selected cycle / image 42 can be represented and grouped together on a single cycle / image 42 presented on the display 48 using indicators 50 to facilitate evaluation of differences between cycles / images 42.

[0041] exist Figure 3AIn this context, indicator 50 is shown as icon 52. Icon 52 has any desired shape and is located on image 42 at a position corresponding to the difference between the value of a single cycle represented by icon 52 and the value of image 42 presented on display 48. Alternatively, as Figure 3B As shown, indicator 50 may take the form of an image line 54, which graphically shows the position of the period / image 42 represented by line 54 relative to the displayed image 42 for global measurement. Using the position of icon 52 or line 54, the user can visually determine the differences between measurements of each individual period / image 42 used to determine the global measurement result, while viewing the period / image 42 that best represents the global measurement, such as the image 42 with the highest image confidence value, image quality value, confidence metric, or a combination thereof. Furthermore, indicator 50 may be a user-selectable link, such as by using a touchscreen or mouse (not shown) connected to control panel 36 of system 10 and forming user input device 43. Figure 1 ), to present the selected image 42 indicated by the indicator 50 on the display 48.

[0042] Furthermore, indicators 50 (e.g., icons 52 or lines 54) may be displayed where the indicators 50 differ from each other in appearance. The differences in the appearance of the individual indicators 50 may represent a confidence measure and / or quality of the image represented by the indicators 50. The differences in the indicators 50 may be selected as needed and may include different colors and / or opacities of the indicators 50. Figure 4A ), or different sizes ( Figure 4B In addition to other suitable distinguishing attributes, the confidence of the global measurement increases as this representation of indicator 50 is combined with the displayed period / image 42 representing the global measurement result and the global measurement result itself, based on the user's ability to easily view the measurements of each individual period / image 42 used to determine the global measurement result.

[0043] According to another exemplary embodiment, instead of finding the period / image 42 that best fits the global measurement (i.e., has the highest image confidence value, image quality value, confidence metric, or a combination thereof), the processing device 44 can create a simulated period / image 42 that fits the global measurement. This simulated period / image 42 can be presented on the display 48 along with an indicator 50 that indicates the measurement value for each selected period / image 42 used to form the global measurement and the simulated period / image 42.

[0044] The processing device 44 has the ability to examine multiple images 42 acquired over multiple cardiac cycles. The methods employed by the processing device 44 are applicable to any measurement that can and / or is expected to be calculated or determined across multiple cycles, to provide the ability to minimize the variability of measurement results while increasing the confidence and reproducibility of the measurement in an easily presented and transparent manner.

[0045] Therefore, the methods disclosed herein provide the following benefits regarding the determination of any measurement, such as, for example, the thickness of the heart wall or a portion of the heart wall, the velocity or volume of blood flow through the heart chambers and / or any vessels surrounding the heart, or other diagnostic measurements used for standard echocardiographic evaluation calculated from ultrasound or echocardiographic imaging across multiple cardiac cycles:

[0046] 1. A method for selecting a period for automatic measurement using any combination of the following:

[0047] a) View recognition;

[0048] b) Automated quality assessment; and / or

[0049] c) Measure confidence level.

[0050] 2. A method for combining measurements using either of the following two methods:

[0051] a) Traditional statistical methods (mean / median); or

[0052] b) The weighted average of the results from any of the methods in (1).

[0053] 3. Global measurement variability measure extracted from the weighted variability of the weighted mixture in (2).

[0054] 4. A method for determining the optimal measurement period for use in (1) is shown to the user.

[0055] 5. A method for visualizing measurement variability results to a user.

[0056] Before describing the components, apparatus, and methods of the present invention, it should be understood that the invention is not limited to the specific embodiments and methods, as these are subject to variation. It should also be understood that the terminology used herein is for the purpose of describing specific exemplary embodiments only and is not intended to limit the scope of this disclosure, which will be limited only by the appended claims.

Claims

1. A method for performing automated echocardiographic measurements across multiple cardiac cycles, the method comprising: An ultrasound imaging system is provided, the ultrasound imaging system including a control panel, a display and a transducer, the control panel including a processing device configured to process ultrasound image data and an electronic storage device containing algorithms for access and utilization by the processing device, the display being operatively connected to the control panel, and the transducer being operatively connected to the control panel to acquire and transmit ultrasound and echocardiogram image data to the control panel; Multiple echocardiographic images were obtained over multiple cardiac cycles; Select a subset of the echocardiographic images; Global measurements are calculated from one or more measurement parameters of the subset of the echocardiographic images; and Display the global measurements. The step of selecting a subset of the echocardiogram images includes applying an image quality algorithm to determine the subset of the echocardiogram images with the lowest image quality.

2. The method of claim 1, wherein the step of selecting a subset of the echocardiographic images comprises applying a view recognition algorithm to the plurality of echocardiographic images to determine the subset of the echocardiographic images, each subset having a stable classification result for a view of the echocardiographic image with high confidence.

3. The method of claim 1, wherein the step of selecting a subset of the echocardiographic images comprises applying a confidence metric to each of the plurality of echocardiographic images.

4. The method of claim 3, wherein the step of applying the confidence metric includes comparing the measurement of each of the plurality of echocardiographic images with a predetermined value of the measurement.

5. The method of claim 1, wherein the step of selecting a subset of the echocardiogram images comprises applying a combination of a view recognition algorithm, the image quality algorithm, and a confidence metric to each of the plurality of echocardiogram images.

6. The method of claim 1, wherein the step of calculating the global measurement comprises averaging the one or more measurement parameters of each subset of the echocardiographic images.

7. The method of claim 6, wherein the step of averaging the one or more measurement parameters includes determining a simple mean / median of the one or more parameters.

8. The method of claim 6, wherein the step of averaging the one or more measurement parameters includes determining a weighted average of the one or more parameters.

9. The method of claim 8, wherein the step of determining the weighted average of the one or more parameters further comprises the following step: Weights are applied to one or more parameters in each subset of the echocardiographic images, wherein the weights of one or more parameters in each subset of the echocardiographic images are obtained from the result of the step of selecting the subset of the echocardiographic images; and The average value is calculated for the weighted one or more parameters of each subset of the echocardiographic images.

10. The method of claim 9, wherein the weight of one or more parameters in each subset of the echocardiographic images corresponds to a value selected from the group consisting of: image confidence value and image quality value, and confidence metric.

11. The method according to claim 1, further comprising the following step: After selecting a subset of the echocardiographic images, a global measurement confidence value is determined; and Display the global measurement confidence value and the global measurement.

12. The method of claim 11, wherein the step of determining the global measurement confidence value includes comparing the confidence measure of each subset of the echocardiographic images with a reference value.

13. The method of claim 11, wherein the step of determining the global measurement confidence value includes determining the variance of the one or more parameters across a subset of the echocardiographic images.

14. The method of claim 1, wherein the step of displaying the global measurement comprises: Displaying a single echocardiographic image; and Displays multiple indicators associated with the single echocardiographic image.

15. The method of claim 14, wherein the single echocardiographic image is an echocardiographic image selected from a subset of the echocardiographic images having the highest image confidence value, image quality value, confidence metric, or a combination thereof.

16. The method of claim 14, wherein the single echocardiographic image is a simulated echocardiographic image generated by the processing device that directly corresponds to the global measurement of the one or more parameters.

17. The method of claim 14, wherein each of the plurality of indicators represents a measurement of one or more parameters relative to the global measurement for each subset of the echocardiographic images.

18. The method of claim 14, wherein each of the plurality of indicators has an appearance corresponding to at least one of: a confidence measure of each of the echocardiographic images in a subset of the echocardiographic images, or a change in the measurement of one or more parameters of each subset of the echocardiographic images relative to the global measurement.

19. An ultrasound imaging system for performing automated measurements from echocardiographic images acquired over multiple cardiac cycles, the echocardiographic imaging system comprising: A control panel, the control panel including a processing device configured to process ultrasound image data and an electronic storage device operatively connected to the processing device; A display, which is operatively connected to the control panel; and A transducer operatively connected to the control panel to acquire and transmit ultrasound image data to the control panel. The processing device is configured to employ one or more automatic measurement algorithms stored in the electronic storage device to select a subset of echocardiographic images from multiple echocardiographic images obtained by the transducer over multiple cardiac cycles based on one or more of an image confidence value, an image quality value, a confidence metric, or a combination thereof; to calculate and display a global measurement of one or more parameters from the subset of echocardiographic images; and wherein the step of selecting the subset of echocardiographic images includes applying an image quality algorithm that determines the subset of echocardiographic images having the lowest image quality.

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