CN113288215B - System and method for measuring cardiac cycle by using ultrasonic image - Google Patents

System and method for measuring cardiac cycle by using ultrasonic image Download PDF

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CN113288215B
CN113288215B CN202011633487.9A CN202011633487A CN113288215B CN 113288215 B CN113288215 B CN 113288215B CN 202011633487 A CN202011633487 A CN 202011633487A CN 113288215 B CN113288215 B CN 113288215B
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ultrasound
heart rate
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similarity
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CN113288215A (en
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任东
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Insight Lifetech Co Ltd
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Insight Lifetech Co Ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
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    • A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
    • A61B8/5223—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for extracting a diagnostic or physiological parameter from medical diagnostic data

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Abstract

The present disclosure relates to a system for measuring a cardiac cycle using an ultrasound image, comprising: the acquisition module is used for acquiring continuous multi-frame ultrasonic images and presetting a plurality of estimated heart rate values, wherein the multi-frame ultrasonic images are acquired in a blood vessel at a preset frequency; the selection module is configured to obtain a plurality of estimated periods based on each estimated heart rate value, take each estimated period as a target period, divide the multi-frame ultrasonic image into a plurality of image groups based on the target period and a preset frequency, and select images at corresponding positions in each image group to form a plurality of image sequences; the calculation module is configured to calculate similarity of two adjacent frames of images in each image sequence and obtain a plurality of similarity values, calculate an average value of the plurality of similarity values as an effective similarity value corresponding to a target period, compare the effective similarity values corresponding to the respective estimation periods, and obtain a cardiac cycle based on the estimation period corresponding to the largest effective similarity value. In this case, the cardiac cycle can be obtained more accurately.

Description

System and method for measuring cardiac cycle by using ultrasonic image
Technical Field
The present disclosure relates to a system and method for measuring a cardiac cycle using an ultrasound image.
Background
Cardiovascular disease has become a leading cause of death worldwide (e.g., coronary heart disease). Blood vessels are currently diagnosed and monitored by ultrasound imaging systems, such as IVUS systems, for ultrasound imaging of the blood vessel. When performing ultrasound imaging, the ultrasound imaging system may produce artifacts due to the motion of tissues or organs (e.g., respiration, heartbeat, etc.), resulting in a reduced quality of the acquired ultrasound images.
In order to obtain a high-quality ultrasound image, the acquired ultrasound image is generally modified by using techniques such as cardiac gating. When the electrocardiographic gating technology is used to correct the ultrasound image, it is often necessary to acquire a heart rate value or a heart cycle of an imaging object of the ultrasound image during imaging, so as to determine a corresponding heart cycle to correct the ultrasound image.
In the prior art, the corresponding heart rate value or heart cycle is often estimated directly from the ultrasound image. However, directly estimated heart rate values or heart cycles are often difficult to match with actual heart rate values or heart cycles.
Disclosure of Invention
The present disclosure has been made in view of the above-mentioned state of the art, and an object of the present disclosure is to provide a system and a method for measuring a cardiac cycle using an ultrasound image, which can obtain a more accurate cardiac cycle.
To this end, a first aspect of the present disclosure provides a system for measuring a cardiac cycle using an ultrasound image, the system for measuring a cardiac cycle using an ultrasound image acquired in a blood vessel, the system comprising: the heart rate prediction system comprises an acquisition module, a selection module and a calculation module, wherein the acquisition module is used for acquiring continuous multi-frame ultrasonic images and presetting a plurality of predicted heart rate values, and the multi-frame ultrasonic images are acquired in a blood vessel at a preset frequency; the selection module is configured to obtain a plurality of estimated periods based on each estimated heart rate value, take each estimated period as a target period, divide the multi-frame ultrasonic image into a plurality of image groups based on the target period and the predetermined frequency, and select images at corresponding positions in each image group to form a plurality of image sequences; the calculation module is configured to calculate similarity of two adjacent frames of images in each image sequence and obtain a plurality of similarity values, calculate an average value of the plurality of similarity values as an effective similarity value corresponding to the target period, compare the effective similarity values corresponding to the respective estimation periods, and obtain a cardiac cycle based on the estimation period corresponding to the largest effective similarity value.
In the disclosure, a plurality of frames of ultrasonic images are obtained through an obtaining module and a plurality of estimated heart rate values are preset, the plurality of frames of ultrasonic images are obtained in a blood vessel at a preset frequency, and the selecting module and the calculating module can process the plurality of frames of ultrasonic images based on the preset frequency and the estimated heart rate values, so that the cardiac cycle corresponding to the plurality of frames of ultrasonic images can be obtained. In this case, the cardiac cycle corresponding to the multi-frame ultrasound image can be obtained more accurately.
In addition, in the system provided in the first aspect of the present disclosure, optionally, the calculating module is further configured to obtain an estimated heart rate value corresponding to the maximum valid similarity value, and obtain the heart rate value based on the estimated heart rate value corresponding to the maximum valid similarity value. In this case, the heart rate value corresponding to the multi-frame ultrasound image can be obtained more accurately.
Further, in the system provided by the first aspect of the present disclosure, optionally, the plurality of frames of ultrasound images are sequentially arranged within the acquisition module to constitute an ultrasound image sequence. Therefore, the ultrasound image sequence can be divided into a plurality of image groups in an advantageous manner.
Further, in the system provided in the first aspect of the disclosure, optionally, each of the plurality of estimated heart rate values is numerically continuous. In this case, subsequent acquisition of a more accurate cardiac cycle therefrom can be facilitated.
Additionally, in the system provided in the first aspect of the present disclosure, optionally, the plurality of estimated heart rate values covers at least a target range of values. In this case, subsequent acquisition of a more accurate cardiac cycle therefrom can be facilitated.
Additionally, in the system provided in the first aspect of the present disclosure, optionally, the selection module acquires a predetermined number of frames based on the target period and the predetermined frequency, and divides the multi-frame ultrasound image into a plurality of image groups based on the predetermined number of frames. Thus, the selection module can be facilitated to divide the multi-frame ultrasound image into a plurality of image groups.
In addition, in the system provided in the first aspect of the present disclosure, optionally, the calculation module is configured to calculate similarities of two adjacent frames of ultrasound images in the corresponding target regions to obtain corresponding similarity values. In this case, the similarity values corresponding to the corresponding target regions of the two adjacent frames of ultrasound images can be obtained in a targeted manner, so that a more accurate cardiac cycle can be obtained subsequently.
Additionally, in the system provided in the first aspect of the present disclosure, optionally, the ultrasound images in each image sequence are arranged in a sequential order in the ultrasound image sequence. Therefore, the similarity values corresponding to the two adjacent frames of ultrasonic images can be conveniently and accurately obtained subsequently.
A second aspect of the present disclosure provides a method of measuring a cardiac cycle using an ultrasound image, which is a method of measuring a cardiac cycle using an ultrasound image acquired in a blood vessel, including: acquiring continuous multi-frame ultrasonic images in a blood vessel at a preset frequency, presetting a plurality of estimated heart rate values, acquiring a plurality of estimated cycles based on the estimated heart rate values, respectively taking the estimated cycles as target cycles, dividing the multi-frame ultrasonic images into a plurality of image groups based on the target cycles and the preset frequency, selecting images at corresponding positions in the image groups to form a plurality of image sequences, calculating the similarity of two adjacent images in each image sequence and acquiring a plurality of similarity values, calculating the average value of the similarity values as an effective similarity value corresponding to the target cycle, comparing the effective similarity values corresponding to the estimated cycles, and acquiring a cardiac cycle based on the estimated cycle corresponding to the maximum effective similarity value.
In the disclosure, continuous multi-frame ultrasound images are obtained in a blood vessel at a predetermined frequency, a plurality of estimated heart rate values are preset, and the multi-frame ultrasound images can be processed based on the predetermined frequency and the estimated heart rate values, so that a cardiac cycle corresponding to the multi-frame ultrasound images can be obtained. In this case, the cardiac cycle corresponding to the multi-frame ultrasound image can be obtained more accurately.
In addition, in the manufacturing method provided in the second aspect of the present disclosure, optionally, an estimated heart rate value corresponding to the maximum valid similarity value is obtained, and the heart rate value is obtained based on the estimated heart rate value corresponding to the maximum valid similarity value. In this case, the heart rate value corresponding to the multi-frame ultrasound image can be obtained more accurately.
According to the present disclosure, a system and method for measuring a cardiac cycle using an ultrasound image, which can obtain a more accurate cardiac cycle, can be provided.
Drawings
Fig. 1 is a block diagram showing a system according to an embodiment of the present disclosure.
Fig. 2 is a schematic structural diagram illustrating an ultrasound imaging system according to an embodiment of the present disclosure.
Fig. 3 is a schematic diagram illustrating an application of an ultrasound imaging system according to an embodiment of the present disclosure.
Fig. 4 is a schematic diagram illustrating acquisition of a multi-frame ultrasound image according to an embodiment of the present disclosure.
Fig. 5 is a schematic diagram illustrating acquisition of a plurality of image sequences based on a multi-frame ultrasound image according to an embodiment of the present disclosure.
Fig. 6 is a flowchart illustrating a method of measuring a cardiac cycle using an ultrasound image according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the following description, the same components are denoted by the same reference numerals, and redundant description thereof is omitted. The drawings are schematic and the ratio of the dimensions of the components and the shapes of the components may be different from the actual ones.
In addition, the headings and the like referred to in the following description of the present disclosure are not intended to limit the content or scope of the present disclosure, but merely serve as a reminder for reading. Such a subtitle should neither be understood as a content for segmenting an article, nor should the content under the subtitle be limited to only the scope of the subtitle.
A system 10 for measuring a cardiac cycle using ultrasound images (see fig. 1) to which the present disclosure relates may measure a cardiac cycle of an imaging subject at the time of acquiring an ultrasound image based on the ultrasound image. With the system 10 for measuring a cardiac cycle using ultrasound images according to the present disclosure, a more accurate cardiac cycle can be obtained.
The system 10 according to the present disclosure is described in detail below with reference to the drawings.
Fig. 1 is a block diagram illustrating a system 10 according to an embodiment of the present disclosure.
In some examples, referring to fig. 1, system 10 may include an acquisition module 110, a selection module 120, and a calculation module 130. The obtaining module 110 may be configured to obtain a multi-frame ultrasound image. The selection module 120 and the calculation module 130 may process the ultrasound images acquired by the acquisition module 110 to acquire a cardiac cycle of an imaging subject while acquiring a plurality of frames of ultrasound images.
In some examples, the acquisition module 110 may acquire a multi-frame ultrasound image. The ultrasound image may be an ultrasound image obtained by imaging the imaging object by the ultrasound imaging system 20 (see fig. 2 to 4). In some examples, ultrasound imaging system 20 may acquire (or generate) ultrasound images at a predetermined frequency. In some examples, the multi-frame ultrasound images acquired by the acquisition module 110 may be filtered from ultrasound images generated by the ultrasound imaging system 20 from the beginning of imaging the imaging subject to the end of imaging. In some examples, the multi-frame ultrasound images may be consecutive. Therefore, the subsequent confirmation of the corresponding cardiac cycle of the multi-frame ultrasonic image can be facilitated. In some examples, the multiple frames of ultrasound images acquired by the acquisition module 110 may be arranged in a certain order to form an ultrasound image sequence L (see fig. 4). This facilitates the subsequent division of the ultrasound image sequence L into a plurality of image groups. In some examples, the frames of ultrasound images within the sequence of ultrasound images L may be arranged in the order in which the ultrasound images were generated by the ultrasound imaging system 20 (i.e., the chronological order of generation of the ultrasound images). In the embodiment according to the present disclosure, the generation time of the ultrasound image arranged further forward in the ultrasound image sequence L may be earlier. For example, the acquisition module 110 may acquire a multi-frame ultrasound image. The multi-frame ultrasound image may be a continuous ultrasound image acquired by the ultrasound imaging system 20 at a predetermined frequency within the blood vessel.
Fig. 2 is a schematic structural diagram illustrating an ultrasound imaging system 20 according to an embodiment of the present disclosure. Fig. 3 is a schematic diagram illustrating an application of the ultrasound imaging system 20 according to the embodiment of the present disclosure.
In some examples, the ultrasound imaging system 20 may be an intravascular ultrasound imaging system. For example, the ultrasound imaging system 20 may acquire an ultrasound image of a blood vessel within the blood vessel (see fig. 3). In this case, the multi-frame ultrasound image may be a blood vessel ultrasound image acquired within a blood vessel. Thus, a plurality of frames of ultrasound images can be used to measure their corresponding cardiac cycle or heart rate values. Examples of the present disclosure are not so limited and, in some examples, the ultrasound imaging system 20 may be an in vitro imaging system. For example, the ultrasound imaging system 20 may ultrasonically image a blood vessel of an imaging subject with B-mode ultrasound or the like to acquire an ultrasound image.
In some examples, the ultrasound imaging system 20 may include an extracorporeal device 210 and an intravascular device 220 (see fig. 2). The extracorporeal device 210 may be connected to the intravascular device 220, and the intravascular device 220 may collect information from the blood vessel and transmit the collected information to the extracorporeal device 210 for processing to generate an ultrasound image. In some examples, the intravascular device 220 may have a distal side distal to the extracorporeal device 210 and a proximal side proximal to the extracorporeal device 210.
In some examples, the intravascular device 220 can include a catheter 221, a drive shaft 222, and a probe 223 (see fig. 2 and 3). Wherein the conduit 221 can have a lumen, and the probe 223 can be coupled to the drive shaft 222 and can move with the drive shaft 222 within the conduit 221. Additionally, the probe 223 may be used for information acquisition within a blood vessel.
In some examples, the intravascular device 220 may be inserted into an imaging subject, such as a blood vessel 30, while the ultrasound imaging system 20 is in operation, for information acquisition within the blood vessel 30 (see fig. 3). Specifically, during an interventional procedure, a medical professional may first puncture a site (e.g., at a radial artery or a femoral artery) on an imaging subject and advance a medical guidewire along the blood vessel to a region to be imaged (e.g., segment AB of blood vessel 30 in fig. 3) within blood vessel 30, then advance catheter 221 along the medical guidewire to the region to be imaged, then advance drive shaft 222 to move within catheter 221 and place probe 223 at target location a; the medical professional may then operate the retraction mechanism 212 to control the retraction and rotation of the drive shaft 222, and the probe 223 may follow the drive shaft 222 and may acquire information within the blood vessel during movement, such as by transmitting and receiving acoustic or optical signals. In this case, the probe 223 may acquire blood vessel information of the region to be imaged, such as blood vessel lumen and wall cross-sectional structure information of the region to be imaged, etc., within the blood vessel. In some examples, the target position a may be a side of the region to be imaged near the distal side.
In some examples, as shown in fig. 1, the conduit 221 may be in the form of an elongated tube. In some examples, the catheter 221 can have a catheter lumen for disposing the drive shaft 222 and the probe 223. In such a case, drive shaft 222 and probe 223 can be disposed within the catheter lumen, and drive shaft 222 and probe 223 can be movable (e.g., translated and rotated) relative to catheter 221. In some examples, the cross-section of the catheter 10 may be circular in shape. Thereby, friction between the catheter 10 and the blood vessel 40 can be reduced, thereby reducing the risk of injury to the blood vessel 40.
In some examples, the drive shaft 222 is flexible. In this case, the drive shaft 222 can be adapted to the catheter 221 to travel in a curved blood vessel, whereby the possibility of damage to the drive shaft 222 can be reduced. In some examples, the drive shaft 222 near the proximal side may be connected with the retraction mechanism 212. Thus, the retraction mechanism 212 can control the retraction and rotation of the drive shaft 222. In some examples, the drive shaft 222 near the distal side can be coupled to the probe 223, the retraction mechanism 212 can retract the probe 223 by controlling the drive shaft 222, the probe 223 can require high speed rotation when retracted, and the drive shaft 222 can be configured to withstand the torsional force applied by the retraction mechanism 212. In some examples, the drive shaft 222 can rotate within the catheter 221 and move relative to the catheter 221, in which case the catheter 221 can remain stationary without rotation and movement, thus reducing damage to the blood vessel.
In some examples, probe 223 may collect information by transmitting and receiving acoustic or optical signals. For example, the probe 223 may be an ultrasound probe that includes an ultrasound transducer. The probe 223 can acquire blood vessel information of a region to be imaged by transmitting and receiving ultrasonic sound beams inside a blood vessel. In some examples, information acquired by the probe 223 may be transmitted to the extracorporeal device 210 for processing. In some examples, the probe 223 may be connected to the extracorporeal device 210 by a connecting wire. In some examples, the connecting wires may be disposed along the drive shaft 222. Examples of the disclosure are not limited thereto, and in some examples, the probe 223 may wirelessly transmit the collected information to the extracorporeal device 210 for processing.
In some examples, referring to fig. 2, extracorporeal device 210 may include a host 211 and a retraction mechanism 212. Wherein, the host 211 can be connected with the withdrawing mechanism 212 to realize the signal transmission between the host 211 and the withdrawing mechanism 212.
In some examples, the retraction mechanism 212 may be coupled to a drive shaft 222 in the intravascular device 220. In some examples, the retraction mechanism 212 may be mechanically coupled with the drive shaft 222. For example, the retraction mechanism 212 may be coupled to the drive shaft 222 by a snap fit or a threaded connection, among others. In this case, the retracting mechanism 212 can control the driving shaft 222 to retract and rotate, and the probe 223 can move along with the driving shaft 222, thereby obtaining an ultrasonic image of the region to be imaged in the blood vessel. For example, referring to fig. 3, the ultrasound imaging system 20 may acquire an ultrasound image of the blood vessel 30 at the AB segment. In some examples, the retraction mechanism 212 controls the retraction rate of the drive shaft 222 to be 0-2 mm/s. For example, the retraction mechanism 212 may control the rate at which the drive shaft 222 is retracted at 0.5, 1, 1.5, or 2mm/s, etc.
Fig. 4 is a schematic diagram illustrating acquisition of a multi-frame ultrasound image according to an embodiment of the present disclosure. Fig. 4(a) is a schematic diagram showing selection of a plurality of frames of ultrasound images from the ultrasound images acquired by the ultrasound imaging system 20. Fig. 4(b) is a schematic diagram showing a plurality of frames of ultrasound images (i.e., ultrasound image sequence L).
In some examples, the host 211 may receive information acquired intravascularly by the intravascular device 220 and process to obtain ultrasound images. In some examples, ultrasound imaging system 20 may acquire ultrasound images intravascularly at a predetermined frequency. In some examples, the predetermined frequency at which ultrasound imaging system 20 acquires ultrasound images may be 0-100 frames/s. That is, the ultrasound imaging system 20 may acquire 0-100 frames of ultrasound images per second. For example, the predetermined frequency of the ultrasound imaging system 20 may be 10, 20, 30, 40, 50, 60, 70, 80, 90, or 100 frames/s. For example, referring to fig. 4(a), the ultrasound imaging system 20 may sequentially acquire an ultrasound image a, an ultrasound image b, an ultrasound image c, and so on at a predetermined frequency until an ultrasound image d is acquired. Wherein, the ultrasound image a may be a first frame ultrasound image acquired by the ultrasound imaging system 20 at a of the blood vessel 30, and the ultrasound image d may be a last frame ultrasound image acquired by the ultrasound imaging system 20 at B of the blood vessel 30. In some examples, as described above, the plurality of frames of ultrasound images acquired by the acquisition module 110 may be filtered from ultrasound images acquired by the ultrasound imaging system 20. For example, referring to fig. 4(a) and 4(b), a plurality of consecutive ultrasound images are selected from the image sequence from the ultrasound image a to the ultrasound image d to constitute the ultrasound image sequence L. In some examples, the acquisition module 110 may acquire a predetermined frequency corresponding to a plurality of frames of ultrasound images. In particular, the acquisition module 110 may acquire a predetermined frequency corresponding to a plurality of frames of ultrasound images as they are generated (or acquired) by the ultrasound imaging system 20.
In some examples, the acquisition module 110 may preset a plurality of estimated heart rate values. In some examples, each of the predetermined plurality of estimated heart rate values may be numerically continuous. In this case, the plurality of estimated heart rate values may cover at least the target range of values. In this case, subsequent acquisition of a more accurate cardiac cycle therefrom can be facilitated. In some examples, the target range of values may be determined based on a normal heart rate range. In some examples, the lower limit of the target value range may be selected from 0 to 60 times/min. In some examples, the lower limit of the target value range may be selected from 100 to 200 times/min. For example, the target value range may be 50 to 150 times/min, 60 to 120 times/min, or 60 to 180 times/min.
In some examples, as described above, system 10 may also include selection module 120. In some examples, the selection module 120 may be connected with the acquisition module 110. In some examples, selection module 120 may acquire a plurality of estimated heart rate values, a plurality of frames of ultrasound images, and a predetermined frequency from acquisition module 110.
In some examples, selection module 120 may obtain a plurality of predicted periods based on respective predicted heart rate values. In some examples, the selection module 120 may obtain an estimated cardiac cycle corresponding to each estimated heart rate value based on each estimated heart rate value, and use the estimated cardiac cycle as the estimated cycle corresponding to the estimated heart rate value. For example, if the estimated heart rate value is 60 times/min, the estimated cardiac cycle is 1s, that is, the estimated cycle is 1 s; if the estimated heart rate value is 120 times/min, the estimated cardiac cycle is 0.5s, namely the estimated cycle is 0.5 s.
Fig. 5 is a schematic diagram illustrating acquisition of a plurality of image sequences based on a multi-frame ultrasound image according to an embodiment of the present disclosure. Fig. 5(a) shows a schematic diagram of dividing the multi-frame ultrasound image shown in fig. 4(b) into a plurality of image groups. Fig. 5(b) shows a schematic diagram of acquiring a plurality of image sequences from the plurality of image groups shown in fig. 5 (a).
In some examples, the selection module 120 may take each of the predicted periods as a target period. In this case, it is convenient to subsequently obtain valid similarity values corresponding to each estimated cycle, so that the cardiac cycle can be obtained.
In some examples, the selection module 120 may divide the multi-frame ultrasound image into a plurality of image groups based on the target period and the predetermined frequency. Thereby, subsequent acquisition of a plurality of image sequences can be facilitated.
In some examples, the selection module 120 may acquire a corresponding number of ultrasound images (i.e., a predetermined number of frames) within the target period based on the target period and a predetermined frequency. In some examples, the selection module 120 may multiply the target period and the predetermined frequency to obtain a corresponding number of ultrasound images within the target period. For example, if the target period is 1s and the predetermined frequency is 30 frames/s, the number of ultrasound images corresponding to the target period may be 30 frames; if the target period is 0.5s and the predetermined frequency is 30 frames/s, the number of ultrasound images in the target period may be 15 frames. Examples of the disclosure are not limited thereto, and in some examples, selection module 120 may individually take each of the estimated heart rate values as a target heart rate value. In some examples, selection module 120 may acquire a corresponding number of ultrasound images (which may be equivalent to a predetermined number of frames) within the estimated cardiac cycle based on the target heart rate value and a predetermined frequency. In some examples, selection module 120 may calculate a ratio of the predetermined frequency to the target heart rate value to obtain a corresponding number of ultrasound images in the estimated cardiac cycle. For example, if the target heart rate value is 60 times/min (corresponding to 1s of the target period) and the predetermined frequency is 30 frames/s, the ratio of the predetermined frequency to the target heart rate value may be 30 frames/time, i.e., the number of ultrasound images corresponding to the estimated cardiac period may be 30 frames (the predetermined number of frames is 30 frames).
In some examples, the selection module 120 may divide the multi-frame ultrasound image into a plurality of image groups based on a predetermined number of frames. Thus, the selection module 120 can facilitate the division of the multi-frame ultrasound image into a plurality of image groups. In some examples, the selection module 120 may continuously select the target frame ultrasound image (e.g., the first frame ultrasound image) from a plurality of frames of ultrasound images, and each time a predetermined number of frames of ultrasound images are selected, the selected frames of ultrasound images are used as a group of images until a plurality of groups of images are acquired. In this case, the number of the respective image groups may be a predetermined number of frames. For example, an ultrasound image sequence may be broken up into a plurality of image groups containing a predetermined number of frames of successive ultrasound images.
Examples of the present disclosure are not limited thereto, and in some examples, the selection module 120 may divide the ultrasound images located after the target frame ultrasound image within the multi-frame ultrasound image into respective image groups. In this case, the number of ultrasound images in the last image group (i.e., the nth image group) may not be greater than the predetermined number of frames. The plurality of image groups can be named according to the arrangement sequence of the first frame of ultrasound image in the ultrasound image sequence in each image group. For example, the first group of images is arranged most forward, and the last group of images is arranged most backward. In some examples, if the number of ultrasound images in the last image group is less than a predetermined number of frames, the selection module 120 may remove the image group and perform subsequent processing on the remaining other image groups. In other examples, if the number of ultrasound images in the last group of images is less than a predetermined number of frames, the selection module 120 may also retain the group of images before processing each group of images.
In some examples, within two adjacent image sets, the last frame ultrasound image within the previous image set and the first frame ultrasound image within the next image set may be consecutive two frames of ultrasound images within the sequence L of ultrasound images. In some examples, the number of image groups may be no less than two. In some examples, the multiple frames of ultrasound images within each image group may be arranged in the order of the sequence L of ultrasound images, respectively. For example, referring to fig. 5(a), the predetermined frame number may be 15 frames, and the total frame number of the multi-frame ultrasound image may be i, wherein the i-th frame ultrasound image may be represented as SiThe selection module 120 may select a 1 st ultrasound image (i.e., S) from the multi-frame ultrasound images1) Initially, a multi-frame ultrasound image is divided into n image groups, where n may be no less than 2. For example, the first image group (i.e., T)1) The internal ultrasound image may be S1～S15The second image group (i.e. T)2) The internal ultrasound image may be S16～S30The nth image group (i.e., T)n) The internal ultrasound image may be Sm～SiEtc., wherein m may be no greater than i. In this case, the number of ultrasound images of the nth image group may not be more than a predetermined number of frames.
In some examples, the selection module 120 may select a plurality of image sequences from each image group. In some examples, the selection module 120 may select ultrasound images at corresponding positions in the respective image groups to form a plurality of image sequences. In some examples, the images at the corresponding positions in the respective image groups may refer to ultrasound images respectively located at the same arrangement position within the respective image groups. In some examples, the number of image sequences may be one or more. In some examples, the number size of the image sequence may be no greater than a predetermined number of frames. For example, the number of image sequences may be equal to the size of the predetermined number of frames. Thereby, the subsequently obtained cardiac cycle can be made more accurate. In this case, the number of ultrasound images in the sequence of ultrasound images may be no less than the largest of the predetermined number of frames corresponding to the plurality of estimated heart rate values. For example, the number of frames of ultrasound images within the sequence of ultrasound images may be at least twice the maximum predetermined number of frames. In some examples, the order of the ultrasound images within each image sequence may be arranged in a sequential order within the ultrasound image sequence L. Therefore, the similarity values corresponding to the two adjacent frames of ultrasonic images can be conveniently and accurately obtained subsequently. In some examples, the ultrasound images located within the same image sequence may be ultrasound images at corresponding positions at respective target periods. That is, the time interval between two adjacent frames of ultrasound images in the same image sequence may be the target period. In some examples, each image sequence may contain several frames of ultrasound images. In some examples, the number of ultrasound images within each image sequence may be no less than 2 frames.
For example, referring to FIG. 5(b), selection module 120 may select from T1、T2、···、TnSelecting the ultrasonic image of the corresponding position to form an image sequence L1Image sequence L2V. image sequence LxAnd the like. X may be the same size as the predetermined number of frames. Wherein the selection module 120 can be respectively selected from T1、T2、···、TnThe first frame of ultrasound images in each group are respectively selected and arranged according to the original sequence (i.e. the arrangement sequence in the ultrasound image sequence L) to form an image sequence L1(ii) a Image sequence L1May be respectively S1、S16And S31And the like. Selection module 120 may select from T1、T2、T3、···、TnRespectively selecting the second frame of ultrasound images in the respective groups and arranging the second frame of ultrasound images in the original order (i.e. the arrangement order in the ultrasound image sequence L) to form the image sequence L2Sequence of images L2May be respectively S2、S17And S32And the like. Selection module 120 may select from T1、T2、T3、···、TnThe X-th frame ultrasound images in the respective groups are respectively selected and arranged according to the original sequence (namely the arrangement sequence in the ultrasound image sequence L) to form the image sequence LxSequence of images LxMay be respectively Sx、Sx+15And Sx+30And the like.
In other examples, the selection module 120 may select a plurality of image sequences from a plurality of frames of ultrasound images (i.e., the sequence of ultrasound images L) according to a predetermined number of frames. In some examples, selection module 120 may obtain a predetermined number of frames, as described above. In some examples, the selection module 120 may select an ultrasound image at a corresponding location from within the multi-frame ultrasound image to obtain a plurality of image sequences. In this case, the frame distance of the ultrasound images of the two adjacent frames at the corresponding positions in the sequence of ultrasound images may be a predetermined number of frames. That is, every two frames of ultrasound images within the sequence of ultrasound images may be located at corresponding positions every predetermined number of framesAn ultrasound image of (a). In some examples, several frames of ultrasound images may be contained within each image sequence. Two adjacent frames of ultrasound images within each image sequence may be separated by a predetermined number of frames in the ultrasound image sequence L. For example, the total frame number of the multi-frame ultrasound images in the ultrasound image sequence L can be i, wherein the i-th frame ultrasound image can be represented as Si. If the predetermined number of frames is 15 frames, the selection module 120 may sequentially select a plurality of image sequences from the ultrasound image sequence L, and the image sequences may be the image sequences L respectively1Image sequence L2V. image sequence L15Etc., the number of the plurality of image sequences may be 15 groups. Wherein the image sequence L1The inner ultrasound images may be S respectively1、S16And S31Etc. of the image sequence L2The inner ultrasound images may be S respectively2、S17And S32Etc. of the image sequence L15The inner ultrasound images may be S respectively15、S30And S45And the like.
In some examples, as described above, system 10 may include calculation module 130. In some examples, the calculation module 130 may be connected with the selection module 120. The calculation module 130 may acquire a plurality of image sequences corresponding to the target period from the selection module 120.
In some examples, the calculation module 130 may be configured to calculate similarity between any two frames of ultrasound images to obtain corresponding similarity values between the two frames of ultrasound images. In the embodiment according to the present disclosure, the greater the similarity value corresponding to two frames of ultrasound images, the higher the similarity between the two frames of ultrasound images. For example, the calculation module 130 may calculate the similarity between the two frames of ultrasound images by using a histogram, a Mean Squared Error (MSE) equation, or a Structural Similarity Index (SSIM) algorithm, and may obtain the similarity value between the two frames of ultrasound images.
In some examples, the calculation module 130 may calculate the overall similarity of the two frames of ultrasound images and obtain corresponding similarity values. In other examples, the calculation module 130 may also calculate the similarity of the respective target regions of the two frames of ultrasound images to obtain corresponding similarity values. In this case, the similarity values corresponding to the corresponding target regions of the two adjacent frames of ultrasound images can be obtained in a targeted manner, so that a more accurate cardiac cycle can be obtained subsequently. For example, the calculation module 130 may use a machine learning algorithm in advance and train with the relevant ultrasound image data, and the calculation module 130 may perform feature matching on the ultrasound image based on the training result to confirm its corresponding target region from the ultrasound image, so as to perform correlation calculation for the corresponding target region. In some examples, the calculation module 130 may calculate the similarity between the sector-shaped regions (i.e., the corresponding target regions) corresponding to the two frames of ultrasound images to obtain corresponding similarity values. In some examples, the sector-shaped area may be at any angle. For example, the calculation module 130 may obtain sector areas of 0 ° to 30 ° corresponding to two frames of ultrasound images, respectively, and calculate similarity between the two sector areas and obtain corresponding similarity values. In this case, the similarity value corresponding to the two sector areas can be used as the similarity value corresponding to the two frames of ultrasound images.
In some examples, the calculation module 130 may calculate similarity of two adjacent frames of ultrasound images in each image sequence to obtain a plurality of similarity values, respectively. Specifically, the calculation module 130 may calculate the similarity between two adjacent ultrasound images in any image sequence to obtain several similarity values corresponding to the image sequence. In this case, the calculation module 130 may obtain a plurality of similarity values corresponding to a plurality of image sequences. For example, the calculation module 130 may calculate the image sequence L1The calculating module 130 can calculate S respectively according to the similarity between two adjacent frames of ultrasound images1And S16To obtain S1And S16A corresponding similarity value; the calculation module 130 may also calculate S separately16And S31To obtain S16And S31Corresponding similarity values, etc. In other examples, the calculation module 130 may randomly select several sets of ultrasound images of two adjacent frames from the sets of image sequences and calculate to obtain corresponding similarity values. In this case, the calculation module 130 may obtain a number of image sequences corresponding to each group of image sequencesA similar value.
In some examples, the calculation module 130 may obtain a valid similarity value based on a plurality of similarity values corresponding to a plurality of image sequences. In some examples, the calculation module 130 may calculate an average value of a plurality of similarity values corresponding to a plurality of image sequences as a valid similarity value corresponding to the target period. Specifically, the calculation module 130 may obtain several similar values corresponding to each image sequence. The calculation module 130 may average a plurality of similarity values corresponding to the plurality of image sequences to obtain an average value corresponding to the plurality of similarity values. The calculation module 130 may use the average value as the valid similarity value corresponding to the target period. In other examples, the calculation module 130 may obtain a median, a minimum, a maximum, or the like from among a plurality of similarity values corresponding to the plurality of image sequences as the valid similarity value.
In some examples, as described above, selection module 120 may respectively take each of the predicted periods as a target period, or selection module 120 may respectively take each of the predicted heart rate values as a target heart rate value. In this case, the calculation module 130 may obtain valid similarity values corresponding to each estimated period or each estimated heart rate value. In some examples, the calculation module 130 may compare the valid similarity values corresponding to each of the predicted cycles or each of the predicted heart rate values, and may select the largest valid similarity value. In some examples, the calculation module 130 may obtain the prediction period corresponding to the largest valid similarity value. In some examples, calculation module 130 may obtain the cardiac cycle based on the predicted cycle corresponding to the largest valid similarity value. For example, the calculation module 130 may use the estimated period corresponding to the maximum valid similarity value as the cardiac period corresponding to the ultrasound image sequence L (i.e., the multi-frame ultrasound images). In this case, the cardiac cycle corresponding to the ultrasound image sequence L can be obtained more accurately.
In other examples, calculation module 130 may obtain an estimated heart rate value corresponding to the largest valid similarity value. In some examples, calculation module 130 may obtain the heart rate value based on the estimated heart rate value corresponding to the largest valid similarity value. For example, the calculation module 130 may use the estimated heart rate value corresponding to the maximum valid similarity value as the heart rate value corresponding to the ultrasound image sequence L (i.e., the multi-frame ultrasound images). In this case, the heart rate value corresponding to the ultrasound image sequence L can be obtained more accurately.
Hereinafter, a method of measuring a cardiac cycle using an ultrasound image according to an example of the present embodiment will be described in detail with reference to fig. 6. Fig. 6 is a flowchart illustrating a method of measuring a cardiac cycle using an ultrasound image according to an embodiment of the present disclosure.
The method for measuring a cardiac cycle using an ultrasound image according to an embodiment of the present disclosure, referring to fig. 6, may include the following steps: acquiring a multi-frame ultrasonic image and a preset frequency, and presetting a plurality of estimated heart rate values (step S10); acquiring a plurality of image sequences from the multi-frame ultrasonic image according to the preset frequency and the estimated heart rate value (step S20); and acquiring effective similar values according to the image sequences, and further acquiring the cardiac cycle corresponding to the multi-frame ultrasound image (step S30).
In this embodiment, the obtaining and processing of the multi-frame ultrasound image, the predetermined frequency, the estimated heart rate value, the image sequence, the effective similarity value and the cardiac cycle in the method may refer to the above-mentioned related descriptions of the multi-frame ultrasound image, the predetermined frequency, the estimated heart rate value, the image sequence, the effective similarity value and the cardiac cycle, respectively.
In step S10, as described above, a plurality of frames of ultrasound images and a predetermined frequency may be acquired, and a plurality of estimated heart rate values may be set in advance.
In some examples, a multi-frame ultrasound image may be acquired in step S10. In some examples, the ultrasound image may be an ultrasound image generated by the ultrasound imaging system 20 imaging an imaging subject. In some examples, the multi-frame ultrasound images may be filtered from ultrasound images generated by the ultrasound imaging system 20 during the time from the beginning of imaging the imaging subject to the end of imaging. In some examples, ultrasound imaging system 20 may acquire ultrasound images at a predetermined frequency. In some examples, the multi-frame ultrasound images may be consecutive. In some examples, a predetermined frequency corresponding to a plurality of frames of ultrasound images may be acquired in step S10. In some examples, a plurality of estimated heart rate values may be preset in step S10. In some examples, the predetermined plurality of predicted heart rate values may be numerically continuous. In some examples, the plurality of estimated heart rate values may cover at least the target range of values. In this embodiment, the setting of the target value range in the method can refer to the above description of the target value range. In some examples, step S10 may be implemented by acquisition module 110 in system 10.
In step S20, a plurality of image sequences are acquired from the multi-frame ultrasound image according to the predetermined frequency and the estimated heart rate value, as described above.
In some examples, in step S20, the respective estimated heart rate values of step S10 may be obtained. In some examples, a plurality of predicted cycles may be obtained based on the respective predicted heart rate values. In some examples, in step S20, each estimated period may be taken as a target period. In some examples, a multi-frame ultrasound image may be divided into a plurality of image groups based on a target period and a predetermined frequency.
In some examples, a predetermined number of frames may be acquired based on the target period and the predetermined frequency. In other examples, each of the estimated heart rate values may be individually defined as a target heart rate value. In some examples, a corresponding number of ultrasound images (which may be equivalent to a predetermined number of frames) within the estimated cardiac cycle may be acquired based on the target heart rate value and the predetermined frequency.
In some examples, a multi-frame ultrasound image may be divided into a plurality of image groups based on a predetermined number of frames. In some examples, ultrasound images (simply "images") at corresponding locations in the respective image sets may be selected to form a plurality of image sequences. In other examples, a plurality of image sequences may be selected directly from the multi-frame ultrasound image (i.e., ultrasound image sequence L) according to a predetermined number of frames.
In the present embodiment, the acquisition and processing of the estimated period, the target period, the predetermined number of frames, the target heart rate value and the image group in the method may refer to the above-mentioned description of the estimated period, the target period, the predetermined number of frames, the target heart rate value and the image group. In some examples, step S20 may be implemented by selection module 120 in system 10.
In step S30, as described above, valid similarity values can be obtained from a plurality of image sequences, and thus the cardiac cycle corresponding to the multi-frame ultrasound image can be obtained.
In some examples, the similarity of the ultrasound images of two adjacent frames in each image sequence may be calculated in step S30 to obtain a plurality of similarity values. In some examples, an average of a plurality of similarity values corresponding to a plurality of image sequences may be calculated as a valid similarity value corresponding to the target period. In some examples, as described above, each of the predicted periods may be individually set as a target period in step S20, or each of the predicted heart rate values may be individually set as a target heart rate value in step S20. In this case, valid similarity values corresponding to each estimated period or each estimated heart rate value can be obtained. The effective similarity values corresponding to the estimated periods or estimated heart rate values can be compared, and the maximum effective similarity value can be selected. In some examples, the cardiac cycle may be obtained based on an estimated period corresponding to a maximum valid similarity value, or the heart rate value may be obtained based on an estimated heart rate value corresponding to a maximum valid similarity value. In this case, the corresponding cardiac cycle or heart rate value of the ultrasound image sequence can be obtained more accurately.
In this embodiment, the acquisition and processing of the similarity value, the valid similarity value, and the maximum valid similarity value in the method may refer to the above-described associated descriptions of the similarity value, the valid similarity value, and the maximum valid similarity value. In some examples, step S30 may be implemented by calculation module 130 in system 10.
While the present disclosure has been described in detail above with reference to the drawings and the embodiments, it should be understood that the above description does not limit the present disclosure in any way. Those skilled in the art can make modifications and variations to the present disclosure as needed without departing from the true spirit and scope of the disclosure, which fall within the scope of the disclosure.

Claims (10)

1. A system for measuring a cardiac cycle using an ultrasound image, the system for measuring a cardiac cycle using an ultrasound image acquired in a blood vessel, comprising: the heart rate prediction system comprises an acquisition module, a selection module and a calculation module, wherein the acquisition module is used for acquiring continuous multi-frame ultrasonic images and presetting a plurality of predicted heart rate values, and the multi-frame ultrasonic images are acquired in a blood vessel at a preset frequency; the selection module is configured to obtain a plurality of estimated periods based on each estimated heart rate value, take each estimated period as a target period, divide the multi-frame ultrasonic image into a plurality of image groups based on the target period and the predetermined frequency, and select images at corresponding positions in each image group to form a plurality of image sequences; the calculation module is configured to calculate similarity of two adjacent frames of images in each image sequence and obtain a plurality of similarity values, calculate an average value of the plurality of similarity values as an effective similarity value corresponding to the target period, compare the effective similarity values corresponding to the respective estimation periods, and obtain a cardiac cycle based on the estimation period corresponding to the largest effective similarity value.
2. The system of claim 1, wherein:
the calculation module is further configured to obtain an estimated heart rate value corresponding to the maximum valid similarity value, and obtain a heart rate value based on the estimated heart rate value corresponding to the maximum valid similarity value.
3. The system of claim 1, wherein:
the multi-frame ultrasonic images are arranged in sequence in the acquisition module to form an ultrasonic image sequence.
4. The system of claim 1, wherein:
each of the plurality of estimated heart rate values is numerically continuous.
5. The system of claim 4, wherein:
the plurality of estimated heart rate values covers at least a target range of values.
6. The system of claim 1, wherein:
the selection module acquires a preset frame number based on the target period and the preset frequency, and divides the multi-frame ultrasonic image into a plurality of image groups based on the preset frame number.
7. The system of claim 1, wherein:
the calculation module is used for calculating the similarity of the two adjacent frames of ultrasonic images in the corresponding target area to obtain the corresponding similarity value.
8. The system of claim 3, wherein:
the ultrasound images in each image sequence are arranged according to the sequence in the ultrasound image sequence.
9. A method for measuring a cardiac cycle using an ultrasound image, which is a method for measuring a cardiac cycle using an ultrasound image acquired in a blood vessel, comprising: acquiring continuous multi-frame ultrasonic images in a blood vessel at a preset frequency, presetting a plurality of estimated heart rate values, acquiring a plurality of estimated cycles based on the estimated heart rate values, respectively taking the estimated cycles as target cycles, dividing the multi-frame ultrasonic images into a plurality of image groups based on the target cycles and the preset frequency, selecting images at corresponding positions in the image groups to form a plurality of image sequences, calculating the similarity of two adjacent images in each image sequence and acquiring a plurality of similarity values, calculating the average value of the similarity values as an effective similarity value corresponding to the target cycle, comparing the effective similarity values corresponding to the estimated cycles, and acquiring a cardiac cycle based on the estimated cycle corresponding to the maximum effective similarity value.
10. The method of claim 9, wherein:
and obtaining an estimated heart rate value corresponding to the maximum effective similarity value, and obtaining the heart rate value based on the estimated heart rate value corresponding to the maximum effective similarity value.
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