DEVICE FOR ACQUIRING DOPPLER ULTRASOUND DATA AND ASSOCIATED METHOD

Abstract

DEVICE FOR ACQUIRING DOPPLER ULTRASOUND DATA AND ASSOCIATED METHOD The invention relates to a device for assisting in the acquisition of ultrasound data, configured to receive in real time ultrasound images acquired by an ultrasound probe connected to said device, and comprising: a first computer, associated with a first memory, for implementing a classifier configured to classify in real time the first ultrasound images received (11) and associate each image with a class (14) to generate a quality indicator (13) based on said associated class (14); a second computer, associated with a second memory, and configured for transmitting an activation command (63) to the ultrasound probe (SECH) to acquire an ultrasound image with a Doppler ultrasound mode. Figure for the abstract: [Fig. 2]

Description

Title of the invention: DEVICE FOR ACQUIRING DOPPLER ULTRASOUND DATA AND ASSOCIATED METHOD Scope of the invention

[0001] The present invention relates to a device and a method for automating and assisting an operator in acquiring ultrasound images. Advantageously, the present invention allows for the automatic determination of a Doppler measurement location on a received ultrasound image. State of the art

[0002] Ultrasound imaging, also known as sonographic imaging, is a medical imaging technique that uses high-frequency waves to visualize two-dimensional structures inside the body of a living subject. Because ultrasound images are taken in real time, these images show the movement of internal organs in the body, such as the movements of the heart during its beat.

[0003] To acquire such images, an ultrasound probe is placed directly on the subject's skin. A thin layer of gel can be applied to the skin to allow the ultrasound waves to pass through the skin from the probe to the inside of the subject's body. The ultrasound images are produced by measuring the reflection of the ultrasound waves off the subject's organs. The amplitude of the reflected waves measured, and the reflection time of this wave, provide the information necessary to reconstruct the ultrasound image.

[0004] During a cardiac ultrasound examination, the operator must know where to place the probe and how to orient it to obtain the desired image. Generally, the desired images from a cardiac ultrasound are images that allow for certain measurements, particularly the dimensions of organs or tissues.

[0005] In order to increase ultrasound examination capacity, the idea arose of relieving cardiologists of the image acquisition task. For example, images can be taken by an operator who records them and then transmits them to a cardiologist who then only has to interpret them. Such an arrangement makes it possible to increase the number of ultrasound examinations a cardiologist can perform. However, it is then necessary to ensure that the ultrasound images are of sufficient quality for interpretation by a cardiologist. The operator may have knowledge of ultrasound, but when they will not be performing the image analysis themselves, there is a need for a device to assist in acquiring such ultrasound images. Furthermore, the operator must not just acquire a single image of sufficient quality, but a sufficiently long sequence of images, for example over a complete heartbeat cycle, so that the cardiologist can make his diagnosis and / or analysis.

[0006] Software-implemented methods are known for guiding the operator in acquiring echocardiographic images of the heart. These methods include evaluating the quality of an image sequence against a particular view and recording such a sequence.

[0007] One drawback of these methods is that it remains difficult for the operator to assess the quality of the image acquired and whether it is sufficient. Another drawback of these methods is that it can be difficult to obtain a sufficiently long sequence of images corresponding to the required quality, further complicating the operator's task, as their image capture will not be validated by the software.

[0008] Furthermore, for certain diagnostic purposes, spectral analysis is often performed to assess the direction of blood flow and measure the velocity of heart valves, vascular lesions, and other pathological lesions (a region of an organ or tissue that has been damaged as a result of injury or disease). Spectral analysis can be performed using continuous wave (CW) or pulsed wave (PW) Doppler, color Doppler, or tissue Doppler imaging (TDI).

[0009] To measure blood flow velocity using spectral analysis, the ultrasound operator defines a region of the ultrasound cone in which the measurement is to be performed, using measurement localization controls that vary depending on the Doppler mode. For CW mode, the operator specifies a Doppler line containing the origin at the apex of the ultrasound cone and a point at the curved base of the cone, and the highest velocity at any point on the line is determined. For PW mode, the operator specifies both a Doppler line and a segment of that line defined by placing a gate to delimit it, and the velocity along that segment of the line is determined.For color Doppler, the operator specifies a window (or region of interest) delimiting a sample volume that lies within a range of depths across a contiguous sequence of scan lines, in order to display the velocity and direction of flow within that sample volume using color. The best placement for these Doppler measurement controls may vary depending on the structure being examined, the suspected pathology, and the cardiac view.

[0010] An additional difficulty for the operator is therefore to correctly position the Doppler measurement site. This difficulty is particularly detrimental to tissue Doppler, commonly used in cardiac examinations, and for which the quality and accuracy of measurements can be influenced by the operator's experience.

[0011] There is therefore a need for a new device to facilitate the operator in taking ultrasound images.

[0012] The invention therefore aims to provide a device and an associated method enabling operators to acquire ultrasound image sequences of sufficient quality, including Doppler measurements, more easily and quickly. Summary of the invention

[0013] The invention relates to a device for assisting the acquisition of ultrasound data, configured to receive in real time ultrasound images acquired by an ultrasound probe connected to said device.

[0014] Said device includes a first calculator, associated with a first memory, to implement a classifier configured to classify in real time the first ultrasound images received and to associate each image with a class to generate a quality indicator according to said associated class.

[0015] Said device includes a second calculator, associated with a second memory.

[0016] In one embodiment, the first calculator and the second calculator are the same calculator.

[0017] The second computer is configured to perform the following steps: • when a sequence of a predefined number of received images includes a rate of images associated with the same class greater than a predefined rate, the determination of the location of at least two different predefined anatomical structures detected in a received ultrasound image; • the determination of a measurement location based on the determined location of said anatomical structures detected; • the transmission to the ultrasound probe connected to said device of a command to activate one or more Doppler ultrasound modes using the determined measurement location.

[0018] One advantage of the invention is that it allows the sequential acquisition of ultrasound images from a desired view followed by the acquisition of Doppler data at a predetermined position on said image. Another advantage is that it allows a non-specialist user to perform Doppler acquisitions of an organ without having to position the Doppler measurement area themselves. This results in an increase in the overall speed of the ultrasound examination, the possibility of performing this examination by non-specialist personnel, and an increase in the reliability of the acquired measurements. Another advantage of the invention is that, by detecting the location of two predetermined anatomical structures, it allows for greater accuracy of the measurement area. Indeed, the detection of two structures improves spatial referencing compared to the detection of a single structure. Preferably, Each anatomical structure comprises a point. Determining the location of two points on the ultrasound image advantageously allows for a more reliable determination of the measurement area.

[0019] In one embodiment, the second computer is configured to, furthermore, perform a step of receiving at least one Doppler ultrasound data produced by the probe using one or more Doppler ultrasound modes.

[0020] In one embodiment, the second computer is configured to, in addition, perform a step of detecting two predetermined anatomical structures on the received ultrasound image.

[0021] In one embodiment, the predefined anatomical structures include a first anatomical structure defined by the junction between a first leaflet of the valve of a ventricle of the heart and the wall of said ventricle and a second anatomical structure defined by the junction between a second leaflet of said valve and the wall of said ventricle of the heart.

[0022] One advantage is to determine two precise anatomical structures allowing a measurement area to be determined based on these two points in a more reliable and precise manner than with the simple detection of an area such as the ventricle of the heart.

[0023] In one embodiment, the device includes a display for, in real time, displaying the first ultrasound images received, at least one Doppler ultrasound data and / or the last generated quality indicator.

[0024] In one embodiment, the determined measurement location includes a measurement point, a measurement line or a measurement surface on a first received ultrasound image.

[0025] In one embodiment, the device includes a third computer, associated with a third memory, and configured to automatically perform the recording of said image sequence in a fourth memory when a sequence of a predefined number of received images includes a rate of images associated with the same class greater than a predefined rate.

[0026] In one embodiment, the second computer is configured to implement the step of detecting at least two anatomical structures appearing in the received ultrasound image once the third computer has executed the step of automatically recording said image sequence.

[0027] One advantage is being able to trigger Doppler measurements once a sequence of non-Doppler ultrasound images has already been acquired.

[0028] In one embodiment, the classifier is configured to classify an image among: a plurality of classes, each representing a particular view of the organ; and at least one class representing a view of insufficient quality.

[0029] In one embodiment, the classifier is implemented by means of a learning function configured from supervised machine learning.

[0030] In one embodiment, the at least one Doppler ultrasound data includes at least one second ultrasound image.

[0031] In one embodiment, the second computer is further configured to perform an automatic recording step of a sequence of multiple images, each comprising the second ultrasound image superimposed on at least one received first ultrasound image. An advantage is the ability to superimpose a non-Doppler black and white ultrasound image with the received ultrasound data to improve visualization for the clinician.

[0032] According to another aspect, the invention relates to a system comprising a device according to the invention and an ultrasound probe adapted to be connected to said device so as to transmit the ultrasound images captured by the probe to the device. The ultrasound probe comprises a Doppler ultrasound probe.

[0033] According to another aspect, the invention relates to a computer program product comprising instructions which lead a device according to the invention to perform the steps according to the invention.

[0034] According to another aspect, the invention relates to a computer program product comprising instructions that lead a device to execute the following steps: • the receipt of the first ultrasound images; • real-time classification of the first ultrasound images received and association of each image with a class to generate a quality indicator based on said associated class; • when a sequence of a predefined number of received images includes a rate of images associated with the same class greater than a predefined rate, the detection of at least two predefined anatomical structures appearing in the received ultrasound image; • the localization to determine the location of each of the said anatomical structures detected in the received ultrasound image; • the determination of a measurement location in relation to the determined location of said detected anatomical structures; • the transmission to an ultrasound probe connected to said device of a command to activate one or more Doppler ultrasound modes using the determined measurement location; • the reception of at least one Doppler ultrasound data produced by the probe using one or more Doppler ultrasound modes.

[0035] According to another aspect, the invention relates to a computer-readable medium, for example a non-transient medium such as a memory, on which the computer program according to the invention is recorded. Brief description of the figures

[0036] Other features and advantages of the invention will become apparent from the following detailed description, with reference to the accompanying figures, which illustrate:

[0037] [Fig-1]: a schematic view of the image displayed by the device's display according to a first embodiment of the invention.

[0038] [Fig.2]: a schematic view of a device according to one embodiment of the invention.

[0039] [Fig.3]: a flowchart representing the different steps of a process according to a method of execution of the invention.

[0040] [Fig.4]: a schematic representation of the core illustrating the two structures predefined anatomical structures to be located on the ultrasound image. These anatomical structures being two points.

[0041] [Fig.5]: a first example of a measurement location generated by a mode of execution of the invention in which said measurement location includes a point 51 equidistant from the two anatomical structures.

[0042] [Fig.6]: a second example of a measurement location generated by a mode execution of the invention in which said measurement location comprises a segment 52 defined by the position of the two anatomical structures according to a predefined rule.

[0043] [Fig.7]: a third example of a measurement location generated by a mode execution of the invention in which said measurement location comprises a surface 53 defined by the position of the two anatomical structures according to a predefined rule. Detailed description

[0044] The invention relates to a method 1000 for assisting in the generation of an ultrasound image sequence. The invention is particularly advantageous for generating an ultrasound image sequence of the heart. Indeed, the heart is an organ subject to a cycle.

[0045] The cardiac cycle consists of two periods: one during which the heart muscle relaxes and fills with blood, called diastole, followed by a period of vigorous contraction and pumping of blood, called systole. After emptying, the heart immediately relaxes and expands to receive another influx of blood returning from the lungs and other body systems, before contracting again to pump blood back to the lungs and these systems. A functioning heart It normally needs to be fully dilated before it can pump effectively again.

[0046] To analyze potential pathologies, it is important for the practitioner to obtain a sequence of images (or a video) of the entire cardiac cycle. The invention advantageously assists the practitioner in acquiring such a sequence of images.

[0047] However, the invention may also find advantages in the ultrasound acquisition of other organs or where a sequence of images is desirable and / or when Doppler ultrasound image acquisitions are required for diagnosis, for example in the field of obstetric ultrasound.

[0048] The invention also relates to an associated device. An example of such a device 1 is illustrated in [Fig.2].

[0049] Device 1 may include a tablet, a smartphone, a computer, or any other device comprising at least one display and a processor associated with memory. According to another aspect, the invention also relates to a system 2 comprising a device 1 according to the invention and a SECH ultrasound probe connected to said device 1.

[0050] In one embodiment, the device 1 comprises software and hardware means for implementing the method according to the invention described below. Said device preferably comprises at least one REC receiver, a classifier, and a display.

[0051] RECEPTION

[0052] In one embodiment, the method includes a step 100 for receiving real-time ultrasound images 11. These ultrasound images 11 are received by a REC receiver of the device. In one embodiment, the REC receiver may include a buffer memory in which the images received by the REC receiver are temporarily stored before transmission.

[0053] The received ultrasound images 11 are preferentially displayed in real time, for example on an AFF display of the device 1. The received ultrasound images 11 can therefore be transmitted to an AFF display for their real-time display.

[0054] In a preferred embodiment, said received ultrasound images are not ultrasound images acquired using a Doppler ultrasound mode.

[0055] The device 1 may include an AFF display such as a screen, for example a monitor screen, a touch tablet or a smart phone (“smartphone” in English).

[0056] The AFF display is connected to the REC receiver and / or the CLASS classifier and / or the CALC processor. The AFF display is configured to display in real time the ultrasound images 11 received by the REC receiver. The AFF display advantageously allows the operator to have real-time feedback on the ultrasound images being acquired. The AFF display is configured to display additional indicators or data, which will be described later in this description. The AFF display shows an image 1 comprising an ultrasound image received 11 by the REC receiver. Preferably, the displayed ultrasound image is the last ultrasound image received by the REC receiver. The AFF display is thus configured to display in real time the images captured by the SECH ultrasound probe connected to the device according to the invention.

[0057] CLASSIFICATION

[0058] In one embodiment, the method includes a classification step 200 of the ultrasound images 11 received by the REC receiver in real time. The classification is performed by a CLASS classifier of the device.

[0059] The classification of an ultrasound image includes the association of said ultrasound image with a class 14, preferably a class from a predefined group of classes.

[0060] In one embodiment, the classification further includes the generation 300 of a quality indicator 13 based on said class associated with the ultrasound image. The quality indicator may be representative of a class or a predefined set of classes.

[0061] In one execution mode, the classification step further includes the generation of a confidence value. The confidence value can represent the confidence level of the classification performed. The confidence value is generated by the CLASS classifier.

[0062] The classification step is preferably performed by a CLASS classifier of the device. By classifier, we mean an algorithmic function executed by a processor or a computer associated with a memory.

[0063] The CLASS classifier is configured to receive images received by the REC receiver.

[0064] The classifier is configured to classify in real time at least a portion of the images received by the REC receiver. The classifier is configured to associate a class with an ultrasound image. The classifier generates a quality indicator 13 based on the associated class. The quality indicator 13 is preferentially associated with the classified ultrasound image.

[0065] Preferably, the device includes image processing means for processing the received images before providing them to the CLASS classifier. These processing means may include image filters or contrast functions.

[0066] Preferably, the CLASS classifier is configured to classify an ultrasound image of the heart among a plurality of classes comprising, on the one hand, classes each representing a particular view of the heart and, on the other hand, a class representing a view of insufficient quality.

[0067] Thus, when an image is classified in a class representing a particular view of the heart, this image is considered to be of sufficient quality to allow the clinician to advantageously perform predefined measurements from these images. Indeed, cardiologists use specific, well-identified views for their diagnoses.

[0068] In one embodiment, each class representing a particular view of the core represents one view among at least: • a view of a parasternal long-axis section • a view of a parasternal short-axis section • a view of an apical section • a view of a subcostal section • a view of a suprasternal section • a view of a right parasternal section

[0069] Each of these views is well known to cardiologists and is used to visualize different parts of the heart, calculate or measure specific data, and identify certain pathologies.

[0070] Each of these views can be characterized by the presence of one or more specific parts of the heart. For example, a parasternal short-axis view is characterized by the presence on the image of the left and right ventricle sections. From this view, the cardiologist can calculate the fractional shortening and pulmonary pressures.

[0071] In one embodiment, the class representing a view of insufficient quality represents ultrasound views of the heart not belonging to one of the specific views of the other classes or the specific ultrasound views listed above, but whose image quality does not allow the necessary measurements to be carried out related to this specific view.

[0072] In one embodiment, the CLASS classifier is implemented by means of a learning function trained using supervised and / or automatic learning. The learning function preferably comprises a neural network. The learning function is preferably trained on a series of labeled echocardiographic images of the heart.

[0073] In one example, the learning function was configured using a training method that involved submitting a plurality of ultrasound images, each associated with a label, to the classifier. In another embodiment, the classifier was trained with ultrasound images of a specific view of the heart of sufficient quality, each image being associated with a label representing said specific view. The classifier was also trained with ultrasound images of views of the heart other than those mentioned above, or not of sufficient quality to allow the cardiologist to perform measurements from these images, each of these images being associated with a quality label representing a view of insufficient quality.Labels may also include information characteristic of an image of an organ, such as a viewing angle and / or size, image quality, the presence of a specific portion of the heart, or the presence of a measurable anatomical contour. Preferably, labels include the name of the particular view of the heart or a name associated with a poor-quality view.

[0074] The CLASS classifier can be executed in a processor which is itself associated with a memory. The CLASS classifier can be stored in a computer-readable medium such as a memory associated with said processor.

[0075] In one embodiment, the ultrasound image classification step includes generating a matching score for each class. The matching score may include a probability that the ultrasound image belongs to each class. The method then includes selecting the class with the highest score. Preferably, the confidence value is generated from said matching score of the class associated with said ultrasound image.

[0076] In one embodiment, the CLASS classifier classifies 100% of the images received in real time.

[0077] In an alternative embodiment, the CLASS classifier is configured to classify only a proportion of received images. The classifier is then configured to classify a subset of the ultrasound images received in real time. This embodiment is particularly advantageous when the classification speed is lower than the image acquisition speed (in images per unit of time).

[0078] In one embodiment, the classification of an ultrasound image includes the classification of the last ultrasound image received. Once that image has been classified, the process again takes the last ultrasound image received. Thus, it is possible that some ultrasound images may not be classified. However, this embodiment advantageously allows for real-time classification of ultrasound images, regardless of the speed of the classifier or the frequency of ultrasound image reception.

[0079] QUALITY INDICATOR

[0080] In one embodiment, the method according to the invention comprises generating and preferably displaying in real time on the AFF display the generated quality indicator 13. Preferably, the displayed quality indicator 13 corresponds to the last generated quality indicator 13 and / or corresponds to a value representative of a predefined number of the last generated quality indicators.

[0081] In one embodiment, this quality indicator 13 is generated by the CLASS classifier. Such a classifier is configured to, upon receiving an ultrasound image of the organ, classify said image into one of the classes mentioned above. The method then includes generating a quality indicator representative of the classification of this image. Said quality indicator can be associated with said classified ultrasound image.

[0082] Alternatively, the quality indicator 13 can be generated by a remote processor connected to the AFF display and receiving information from the classifier.

[0083] The display of the quality indicator 13 may include a colored indicator whose color depends on the class associated with the classified ultrasound image. The color of the indicator may be representative of a single class. Preferably, the color of the colored indicator may have two distinct colors: a first color representing a group of classes including the classes representing a particular view of the organ, such as one of the particular views of the heart mentioned above, and a second color representing a class representing a view of insufficient quality. Thus, the operator can advantageously determine more quickly whether the ultrasound image being acquired is of sufficient quality or not.

[0084] In one embodiment, the classifier is also configured to generate a confidence value 21 when it receives an ultrasound image of the organ. The confidence value 21 may represent a level of certainty that the image has been correctly classified. In one embodiment, the quality indicator may include this confidence value. The confidence indicator 21 is preferably displayed by the AFF display.

[0085] The quality indicator 13 associated with the classified image may include said confidence indicator. In another alternative mode, a confidence indicator representative of the confidence value is generated and displayed in real time.

[0086] In a first example illustrated in [Fig. 1], the displayed quality indicator 13 includes a colored frame, which preferentially extends around the displayed ultrasound image. The operator can then advantageously visualize whether the image being acquired is indeed the expected one without having to look away from the image. The confidence indicator can be displayed as a numerical value as illustrated in [Fig.1].

[0087] In a second example illustrated in [Fig. 3], the quality indicator 13 includes a color indicator. The color of the color indicator is representative of the classification of the last ultrasound image. At least one of the dimensions of said color indicator is a function of the confidence level. In the example illustrated in [Fig. 3], the quality indicator 13 is a bar whose length varies according to the confidence level and whose color depends on the class associated with the last ultrasound image.

[0088] Such an indicator advantageously allows the operator to visualize whether the image being acquired is of sufficient quality and also allows them to see, without looking away, whether the indicator is degraded or improved depending on the movement of the SECH ultrasound probe. The benefit of such an indicator is that it allows the operator, when slightly moving the probe, to visualize whether this movement increases or decreases the confidence value, and consequently increases or decreases their chances of obtaining a validated image sequence as described below.

[0089] SEQUENCE

[0090] In one embodiment, the method includes the automatic recording 400 of a sequence 20 of images in a MEM memory. This sequence 20 is automatically recorded when a sequence of a predefined number of received or classified images contains a proportion of images associated with the same class 14 greater than a predefined proportion. Preferably, said class is a class representing a particular view of the core.

[0091] By "image sequence" is meant a series of ultrasound images that follow one another in the chronological order of their acquisition. The term "video sequence" will therefore also be used to designate such a sequence of images.

[0092] Thus, when a sufficiently long video includes, for example, a majority of ultrasound images classified in the same class representing a particular view of the organ, the video sequence is automatically recorded in memory. This automatic recording advantageously generates videos of a particular view of the organ automatically, which can then be analyzed by a cardiologist without operator validation.

[0093] The predefined number of received or classified images can be understood as a predefined minimum duration, provided that the image acquisition frequency of the SECH ultrasound probe is constant. The advantage of this threshold is to ensure that the video sequence is long enough to be analyzed by a cardiologist. In another embodiment, the predefined number of images can be replaced by a number of received or classified images. The predefined number can be configured to match a predefined number of cardiac cycles of the subject's heart.

[0094] The ratio of images associated with the same class in said video sequence exceeding a predefined ratio advantageously allows for automatic recording despite a negligible number of images in said sequence lacking sufficient quality. Indeed, this negligible number of images in a video sequence may stem from a classification error or noise related to a particular image. This tolerance advantageously represents a good compromise between the ease of automatic sequence generation and the quality of said sequence.

[0095] In one execution mode, the predefined rate is at least greater than 50%. In another execution mode, the predefined rate can be set by the operator, for example via a user interface of the device.

[0096] In one execution mode, the automatic recording step includes buffering the continuously received ultrasound images and the generated quality indices associated with said images. In this way, when a video sequence meeting the criteria stated above is detected, the images belonging to this sequence can be transferred from the buffer to another memory location, and / or grouped into a single file to generate a video sequence.

[0097] For the sake of clarity, in the remainder of this description, the generation and recording of such a sequence will be referred to as the “validation” of such a sequence.

[0098] TIME INDICATOR

[0099] In one execution mode, the method includes a step of generating and displaying in real time a time indicator 12.

[0100] The displayed time indicator 12 is representative of the number of images remaining to be received or classified to reach a sequence of a predefined number of received images comprising a rate of images associated with the same class greater than a predefined rate.

[0101] This indicator advantageously allows the operator to visualize the time remaining to validate a video sequence of a particular view of the organ. This indicator advantageously allows the operator to visualize the remaining time during which they must maintain an ultrasound image of sufficient quality, said quality being displayed by the quality indicator 13 and / or the confidence indicator.

[0102] The time indicator 12 may include a numerical value such as a countdown. The time indicator 12 may include a gauge that fills or empties depending on the time remaining to validate a video sequence.

[0103] In one embodiment, the method includes, when a first image is classified in a class representing a particular view of the organ, the automatic generation and display of the time indicator 12.

[0104] With each new classified image, the temporal indicator 12 is preferentially updated in real time:

[0105] - if the number of images classified since the first image includes a rate of images associated with the same class which is greater than the predefined rate, then the time indicator 12 is updated by indicating the remaining time or number of images remaining to be received to reach the predefined number of images and the recording of the video sequence 20;

[0106] - if the number of images classified since the first image includes a rate of images associated with the same class which is lower than the predefined rate, then the time indicator 12 is updated to indicate the failure of the validation, for example by resetting the counter or gauge or by the disappearance of the display of such a counter or gauge.

[0107] The method includes the real-time display of received ultrasound images, the quality indicator 13, and optionally the time indicator 12. Such a display is described below with reference to [Fig. 2]. The image displayed by the AFF display includes the ultrasound image 11 received in real time or acquired in real time by the SECH ultrasound probe, the quality indicator 13, and the time indicator 12.

[0108] DOPPLER MEASUREMENT

[0109] The method includes generating a command for activating one or more Doppler ultrasound modes.

[0110] By "Doppler ultrasound mode" (or "Doppler mode") is meant the acquisition of ultrasound data to measure the speed and / or direction of blood flow based on the Doppler effect, in particular the change in frequency of sound and ultrasound waves reflected by a moving object (in this case, blood cells or heart walls).

[0111] The various Doppler modes that can be used include continuous wave Doppler, pulsed wave Doppler, color Doppler, power Doppler, or tissue Doppler, or a combination of each of the preceding modes. In one embodiment, the method includes a step of detecting at least two predefined anatomical structures 35, 34 appearing on the received ultrasound image 11.

[0112] The step of detecting on the image the at least two predefined anatomical structures can be implemented by any algorithm or computer-implemented method known to those skilled in the art, such as an image segmentation algorithm, a feature detection algorithm, or a shape analysis algorithm.

[0113] The method further includes a step of determining the location of each of the at least two anatomical structures in the received ultrasound image.

[0114] In one execution mode, the detection step and / or the location determination step, on the image, of at least two predefined anatomical structures can be implemented by any computer-implemented algorithm or method known to those skilled in the art, such as an image segmentation algorithm, a feature detection algorithm, or a shape analysis algorithm.

[0115] Preferably, the location determination includes generating at least one coordinate for each anatomical structure. These coordinates advantageously represent a position of said anatomical structure on the acquired image.

[0116] Preferably, the received ultrasound image 11 represents one of the particular views of the heart described above on which the two predefined anatomical structures appear.

[0117] In a preferred embodiment, each anatomical structure is defined by a characteristic point of the predefined organ such as a junction between two anatomical elements.

[0118] The advantage of determining on an ultrasound image the position on said image of two anatomical structures held by each by a point is to allow the determination of the location and orientation of a Doppler measurement location.

[0119] In a preferred example illustrated in [Fig. 4], a first anatomical structure 35 is defined by the point of junction between a first leaflet 33 of the mitral valve 31 of the left ventricle 39 of the heart and the wall 36 of said ventricle. Similarly, the second anatomical structure 34 is preferably defined by the point of junction between a second leaflet 32 ​​of said valve of said ventricle 39 of the heart and the wall 37 of said ventricle.

[0120] An advantage of determining the location on the received ultrasound image 11 is to allow the determination of a Doppler measurement location more precisely, in particular on the orientation of a measurement segment or measurement surface.

[0121] Indeed, this localization of two specific points advantageously leads to a better precision in defining the measurement location.

[0122] In another alternative mode, the at least two characteristic points of the predefined organ define a surface, preferably a surface of an anatomical element such as a wall.

[0123] In a particularly preferred embodiment, the determination of the location of at least two anatomical structures is carried out using a learning function trained or configured to receive as input an ultrasound image 11 and generate as output the locations on said image of different predefined anatomical structures to be detected and located. The learning function preferably includes a neural network.

[0124] In one example, the learning function was configured using supervised and / or automatic learning, including submitting to the classifier a plurality of ultrasound images, each associated with at least one label. The at least one label associated with each training ultrasound image includes the location, on the training ultrasound image, of each predefined anatomical structure.

[0125] In one embodiment, said neural network of the learning function comprises a convolutional neural network (better known by the English acronym "CNN" for "Convolutional Neural Network") or more precisely a U-NET.

[0126] Preferably, said learning function is the same as that implemented by the classifier. Thus, each training image includes both at least one label corresponding to a class representing a particular view of the organ and at least one label including the location, on the ultrasound training image, of each predefined anatomical structure.

[0127] The said learning function of the classifier is in this case configured to, from an ultrasound image, classify said image among a plurality of classes and to generate the location of each predefined anatomical structure.

[0128] An advantage of such a function is to allow the user to know if the acquired ultrasound image is of sufficient quality and at the same time to determine the Doppler measurement location on said image with a faster calculation speed and adapted to real time.

[0129] DETERMINATION OF MEASUREMENT LOCATION

[0130] In another step, the method includes determining a Doppler measurement location.

[0131] The measurement location may include a measurement point, a measurement segment and / or a Doppler measurement surface on said ultrasound image.

[0132] The measurement location is determined from the position or location of each anatomical structure previously determined on the received ultrasound image 11.

[0133] The measurement location is defined by coordinates on the ultrasound image, preferably by coordinates relative to the positions on the ultrasound image of the at least two anatomical structures detected.

[0134] In one example, the measurement location is determined based on a point equidistant between the two anatomical structures detected on the ultrasound image.

[0135] One advantage is to allow the positioning of the measurement location to be at much more precise anatomical positions on the ultrasound image.

[0136] In the first example illustrated in [Fig.5], the measurement location includes a measurement point 51. The relative position of said measurement point 51 is determined by a relative position with respect to the two detected anatomical structures 34, 35.

[0137] In a second example illustrated in [Fig. 6], the measurement location comprises a measurement segment or line 52 whose position and orientation are predefined relative to the position of the two anatomical points. The measurement segment 52 is defined by two endpoints 521 and 522 such that the Doppler measurement allows the blood velocity to be measured between these two endpoints.

[0138] In a third example illustrated in [Fig. 7], the measurement location includes a Doppler color box 53, i.e., a measurement area on the ultrasound image. The size, position, and orientation of said Doppler color box 53 are determined based on the relative positions of the two detected anatomical structures.

[0139] The present invention is particularly effective in the second and third examples since determining the position of two anatomical structures on the ultrasound image 11 makes it possible to accurately determine the orientation of the Doppler measurement location. A traditional method using only the detection of one organ (for example, the mitral valve or the ventricle) does not allow the orientation of the measurement location to be generated with similar accuracy and requires intervention by a specialist or additional measurements to correct the position and orientation of the Doppler measurement location.

[0140] In one embodiment, the method includes a step of transmitting TR information based on the Doppler measurement location to the SECH ultrasound probe. This transmission allows the ultrasound probe to generate a Doppler measurement based on the previously determined measurement location.

[0141] This information may include a control signal transmitted to the ultrasound probe, triggering the activation of one or more Doppler ultrasound modes using the measurement location. In this way, the ultrasound probe uses the measurement location to perform ultrasound measurements in Doppler mode.

[0142] In one embodiment, the method comprises the acquisition of Doppler ultrasound data. Preferably, this step is implemented by the SECH ultrasound probe using at least one Doppler ultrasound mode. Said SECH ultrasound probe acquires Doppler signals in accordance with the transmitted control signal.

[0143] Doppler ultrasound data are acquired from the emission, by the ultrasound probe, of ultrasonic signals and the reception of said signals Reflected ultrasonic waves. The emitted signals are emitted in accordance with the control signal so that the ultrasonic signals are reflected in an area corresponding to the predetermined measurement location.

[0144] Doppler ultrasound data preferably include Doppler images, a color map, or any type of data from Doppler measurement such as speed and / or direction information.

[0145] In one embodiment, the device is configured to acquire a succession of ultrasound images 11 and a succession of Doppler data intermittently. An advantage is that it allows the acquisition of Doppler data over a significant time period while simultaneously redefining the measurement location using the acquired ultrasound images.

[0146] In one embodiment, the device is configured to acquire a second sequence. This second sequence comprises a plurality of second ultrasound images formed from the Doppler ultrasound data. The device is preferably configured to record such a second sequence in a device memory and / or to transmit said sequence to a remote device.

[0147] In one embodiment, the localization step of at least two anatomical structures is implemented when at least one first received ultrasound image is classified into a predetermined class.

[0148] In an alternative embodiment, the localization step of at least two anatomical structures is implemented when the sequence of first ultrasound images 20 is automatically generated and / or recorded. In an example illustrated in [Fig. 3], the recording or acquisition of said sequence 20 automatically triggers a trigger instruction 62 for the localization step LOC.

[0149] In an alternative or cumulative embodiment also illustrated in [Fig.3], The LOC localization step of at least two anatomical structures is implemented by the transmission of an instruction 61 by the user through a user interface of the device.

[0150] In one embodiment, the device is configured so that the recording of said sequence 20 automatically generates an alert to the user. In one example, said recording can generate a message inviting the user to initiate the various steps for generating the TR transmission of the Doppler ultrasound mode activation command. The user can then confirm the invitation via a user interface to generate the simplified instruction 61.

[0151] PROGRAM

[0152] According to one embodiment, the method according to the invention comprises selecting a first class from among the classes representing a particular view of the core such as one of the views mentioned above.

[0153] Selecting the first class generates the display on the AFF display of a first pre-recorded ultrasound image 15 of the heart representing such a view. Preferably, the label 17, which may include the name of said particular view, is also displayed on the AFF display. Selecting the first class also generates the display of a first instruction image 14. The first instruction image 14 is preferably pre-recorded. The instruction image illustrates an instruction for the position and / or orientation of the SECH ultrasound probe on a patient to obtain said view corresponding to the selected class. The operator is thus advantageously guided and assisted in acquiring such a view. On the same AFF display, the operator can thus visualize an example of the view to be acquired, the position and orientation of the probe to achieve it.Finally, the operator can view in real time whether the image being acquired is of sufficiently good quality using the quality indicator 13, and can advantageously visualize the influence of the movements he makes on the quality of the acquired image thanks to the confidence indicator.

[0154] Finally, once the operator has found an image of satisfactory quality, they are assisted in real time by the time indicator 12, which represents the time during which they must hold the probe to acquire images of sufficient quality. The operator is also assured, by visualizing the time indicator 12, that a first sequence 20 will be recorded while maintaining its position.

[0155] Once the first sequence has been recorded or validated, the method may include the automatic selection of a second class from among the classes representing a particular view of the heart, such as one of the views mentioned above. Again, the selection of said second class automatically generates the display of a second pre-recorded setpoint image and the display of a second pre-recorded ultrasound image illustrating an ultrasound view.

[0156] According to one embodiment, the method further comprises generating and displaying a progress indicator 18. The progress indicator may be representative of the number of sequences that have been recorded. For example, the progress indicator may be representative of the number of classes representing a particular view of the core for which an image sequence 20 has been automatically generated and / or recorded according to the method of the invention.

[0157] According to one embodiment, the method includes displaying the recorded sequence and further includes a second manual validation by the operator after displaying said sequence.

[0158] According to one embodiment, the method comprises the localization, on the received ultrasound image, of at least two predefined anatomical structures and the determination of the location of each of said anatomical structures.

[0159] The method includes determining a measurement location based on the location of said anatomical structures.

[0160] According to one embodiment, the method comprises transmitting to an ultrasound probe a command to activate at least one Doppler ultrasound mode. This command is generated based on the determined measurement location so as to cause the probe to perform a Doppler ultrasound at the determined measurement location.

[0161] According to one embodiment, the method includes a Doppler ultrasound measurement performed using the ultrasound probe from the previously generated command.

[0162] According to one embodiment, the method includes receiving at least one Doppler ultrasound data from the signals acquired by the ultrasound probe during the Doppler ultrasound measurement.

[0163] DEVICE

[0164] According to one aspect, the device according to the invention comprises software and hardware means for implementing the process as described above.

[0165] An embodiment of the device according to the invention is now described with reference to [Fig.2].

[0166] The device includes a REC receiver. The REC receiver is intended to be connected to a SECH ultrasound probe so as to continuously and in real time receive ultrasound images 11 acquired by said SECH ultrasound probe.

[0167] The REC receiver can be connected to the SECH ultrasound probe by a wired or wireless connection, for example by a Bluetooth connection or a WLFI connection or any other data exchange protocol known to those skilled in the art.

[0168] The REC receiver may include or be associated with one or more memory units for temporarily storing received images. The REC receiver is directly or indirectly connected to the AFF display to transmit the acquired ultrasound images to the AFF display.

[0169] The device further includes means for implementing a CLASS classifier as described above. The classifier is configured to receive the ultrasound images 11, associate a class 14 with the ultrasound images in real time, and generate the quality indicator 13 in real time. The classifier is directly or indirectly connected to the AFF display to transmit the generated indicators to the AFF display.

[0170] According to an alternative, the classifier is implemented by remote electronic equipment, such as a remote server. In this case, the device includes an interface for exchanging data with the remote equipment in order to transmit data and retrieve the result of the processed, i.e., classified, data.

[0171] Finally, in the present invention, it is understood that when the classification is implemented wholly or partly by remote equipment, the device of the invention can be interpreted as the system comprising on the one hand the local device described in this application and the remote means enabling the classification function to be implemented.

[0172] The device further comprises at least one processor or CALC unit associated with memory for performing at least some of the steps of the method according to the invention. For example, a first processor may be configured to perform the steps of classification 200, generation and display of the quality indicator 300 and the time indicator 500, and / or automatic recording 300 of the image sequence 20. For example, a second processor may be configured to perform the steps for generating and transmitting an activation command 63 and receiving at least one Doppler ultrasound data point. In one embodiment, the first and second processors are the same processor. This processor may be connected to the AFF display to transmit the time indicator 12 to the AFF display.In one embodiment, at least one processor or computer includes means for transmitting and receiving information with a remote device, for example via an internet network, enabling the steps of the method according to the invention to be implemented.

[0173] In some cases, the processor or computer can communicate with one or more external devices via the network. The processor or computer can be connected to the network via a wired connection (e.g., via an Ethernet cable) and / or a wireless connection (e.g., via a Wi-Fi network). These external devices can include servers, workstations, and / or databases. The processor or computer can communicate with these devices to, for example, offload computationally intensive tasks. For example, the processor or computer can send an ultrasound image via the network to the server for analysis (e.g., to identify an anatomical feature in the ultrasound or to perform its classification, to detect or determine the position of one or more anatomical structures, to determine the measurement location) and receive the results of the analysis from the server.In addition (or alternatively), the processor or computer can communicate with these devices to access. to information that is not available locally and / or to update a central information repository.

[0174] Device 1 may also include a plurality of processors, each associated with one or more memories, and configured to perform such steps together. In one embodiment, the processor(s) may be remote and connected to the display via a data network.

[0175] The device further comprises one or more memories for storing or recording the sequences generated by the method according to the invention and / or for storing the computer programs that, when executed by one or more processors, implement the method according to the invention. In one embodiment, the device further comprises an EMM transmitter connected to said MEM memory for transmitting said sequences recorded on said MEM memory to a data network. In another embodiment, the device further comprises a second EMM2 transmitter connected to the SECH ultrasound probe for transmitting said activation command 63 to said probe.

[0176] The device may further include means of communication such as transmitters and receivers for the exchange of information with the probe and / or a remote device.

[0177] The AFF display may include means for receiving the various information 11, 13, 21, 12, 63, 64 received by the various means REC, CLASS, PROC of the device to generate the final image to be displayed.

Claims

Demands

1. A device (1) for assisting the acquisition of ultrasound data, configured to receive in real time ultrasound images (11) acquired by an ultrasound probe (SECH) connected to said device (1), and comprising: • a first computer, associated with a first memory, for implementing a classifier (CLASS) configured to classify in real time the first ultrasound images received (11) and associate with each image a class (14) to generate a quality indicator (13) according to said class (14) associated;• a second calculator (CALC2), associated with a second memory, and configured to perform the following steps: • when a sequence of a predefined number of received images includes a rate of images associated with the same class greater than a predefined rate, the determination of the location of at least two different predefined anatomical structures (35, 34) detected in a received ultrasound image; • the determination (DET2) of a measurement location (51, 52, 53) based on the determined location of said anatomical structures (34, 35) detected; • the transmission (TR) to the ultrasound probe (SECH) connected to said device (1) of an activation command (63) of one or more Doppler ultrasound modes using the determined measurement location (51, 52, 53). • the reception (CR) of at least one Doppler ultrasound data (64) produced by the probe using one or more Doppler ultrasound modes.;

2. A device according to claim 1, wherein the predefined anatomical structures comprise a first anatomical structure defined by the junction between a first leaflet of the valve of a ventricle of the heart and the wall of said ventricle and a second anatomical structure defined by the junction between a second leaflet of said valve and the wall of said ventricle of the heart.

3. Device according to claim 1, further comprising a display (AFF) for, in real time, displaying the first ultrasound images, at least one Doppler ultrasound data (64) and / or the last generated quality indicator.

4. Device according to any one of the preceding claims, characterized in that the determined measurement location comprises a measurement point (51), a measurement line (52) or a measurement surface (53) on a first received ultrasound image.

5. Device according to claim 1, further comprising a third computer (CALC3), associated with a third memory, and configured to automatically perform the recording of said image sequence (20) in a fourth memory (MEM) when a sequence of a predefined number of received images includes a rate of images associated with the same class greater than a predefined rate.

6. Device according to claim 5, wherein the second computer (CALC2) is configured to implement the step of detecting at least two anatomical structures appearing in the received ultrasound image once the third computer has executed the step of automatically recording said image sequence (20).

7. Device according to claim 1, wherein the classifier (CLASS) is configured to classify an image among: • a plurality of classes, each representing a particular view of the organ; and • at least one class representing a view of insufficient quality.

8. Device according to claim 7, wherein the classifier (CLASS) is implemented by means of a learning function configured from supervised machine learning.

9. Device according to any one of the preceding claims, characterized in that at least one Doppler ultrasound data point (64) comprises at least one second ultrasound image.

10. System (2) comprising a device (1) according to any one of claims 1 to 9 and an ultrasound probe (SECH) capable of being connected to said device (1) so as to transmit the ultrasound images captured by the probe to the device.

11. Product computer program comprising instructions that cause a device to perform the following steps: • receiving initial ultrasound images (11); • real-time classification of the initial received ultrasound images (11) and association of each image with a class (14) to generate a quality indicator (13) based on said associated class (14); • when a sequence of a predefined number of received images includes a rate of images associated with the same class greater than a predefined rate, the detection (DET) of at least two different predefined anatomical structures appearing in a received ultrasound image; • localization (LOC) to determine the location of each of said detected anatomical structures in the received ultrasound image; • determination (DET2) of a measurement location relative to the determined location of said detected anatomical structures;• the transmission (TR) to an ultrasound probe (SECH) connected to said device (1) of an activation command for one or more Doppler ultrasound modes using the determined measurement location; • the reception (RC) of at least one Doppler ultrasound data (64) produced by the probe using one or more Doppler ultrasound modes.

12. Computer-readable medium on which the computer program according to claim 11 is recorded.

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