Image processing method and system for intravascular ultrasound

Abstract

The application provides an intravascular ultrasound image processing method and system. The intravascular ultrasound image processing method is processed frame by frame on the intravascular ultrasound image, the translation component and the rotation component in the imaging process are calculated and obtained according to the translation and rotation between two adjacent frames caused by heartbeat, so as to correct the collected intravascular ultrasound image. The application removes the translation and rotation between images while retaining the irregular shape of the blood vessel itself, reduces the calculation complexity of the heartbeat frequency extraction based on the image, and considers the influence of the heartbeat harmonic, so that the heartbeat motion compensation is more accurate.

Description

Technical Field

[0001] This invention belongs to the medical field, and particularly relates to an image processing method for intravascular ultrasound and a system for applying the intravascular ultrasound image processing method. Background Technology

[0002] Intravascular ultrasound (IVUS) is an imaging technique widely used for assessing atherosclerotic plaques. The signal acquisition process involves inserting an imaging catheter into the blood vessel, with an ultrasound probe at the end of the catheter rotating and retracting at a constant, known speed to record information about the internal structure of the lumen. However, during the retraction imaging process, the imaging probe is affected by the periodic heartbeat, resulting in displacement and rotational shifts. This manifests as misalignment of the vascular structure in cross-sectional images and a jagged shape in longitudinal images of the vessel's appearance. Therefore, it hinders the longitudinal visualization of vascular morphology, volume measurement, and accurate assessment of any image-derived morphological structures.

[0003] The earliest proposed heartbeat compensation method was online electrocardiogram gating, which utilizes electrocardiogram signals to acquire only IVUS images during the end-diastolic phase of the heartbeat, assuming that the images at this stage are unaffected by cardiac motion. Compared to standard IVUS acquisition time, this procedure increases the acquisition time by three times. Furthermore, it requires simultaneous extraction of electrocardiogram signals during IVUS image acquisition, placing certain demands on the acquisition equipment.

[0004] To address the shortcomings of online ECG gating methods, image-based gating has been proposed. This method typically consists of three steps: generating a signal measuring cardiac motion for each frame; filtering and extracting local extrema from the motion signal; and offline gating of the end-diastolic phase. Compared to online ECG gating, image-based gating is independent of the ECG signal and has no additional requirements for IVUS acquisition equipment. However, all gating methods extract only images from specific phases of the IVUS image sequence, discarding a significant amount of valid data.

[0005] Furthermore, to preserve the complete image sequence, a heartbeat motion compensation method based on registration has been proposed. Early studies used block matching strategies, maximum likelihood estimation, absolute difference, rigid registration, sum-of-squares difference, or standardized cross-correlation to rigidly register adjacent IVUS images. However, these methods are severely affected by speckle noise, which greatly reduces the accuracy of registration. Therefore, a method to achieve registration by aligning the geometric center or centroid of the lumen in adjacent images has been proposed. This method is less affected by speckle noise and can significantly improve registration accuracy. However, existing methods of this kind, after aligning the centroid of the image sequence, remove the irregular shape of the blood vessels themselves along with the influence of heartbeat motion, which will affect the accuracy of subsequent analysis.

[0006] In view of this, it is indeed necessary to propose an image processing method and system for intravascular ultrasound to solve the above problems. Summary of the Invention

[0007] The purpose of this invention is to provide an image processing method and system for intravascular ultrasound. This method processes intravascular ultrasound images frame by frame, calculating the translation and rotation components during the imaging process based on the translation and rotation between adjacent frames caused by heartbeats, thereby correcting the acquired intravascular ultrasound images. This invention preserves the irregular shape of the blood vessel while removing the translation and rotation between images, reduces the computational complexity of heartbeat frequency extraction based on the image, and considers the influence of heartbeat harmonics, resulting in more accurate compensation for heartbeat motion.

[0008] To achieve the above-mentioned objective, the present invention provides a method for processing intravascular ultrasound images, comprising the following steps: acquiring an intravascular ultrasound image of a target vascular segment; segmenting the intravascular ultrasound image frame by frame; and acquiring a cross-sectional image I corresponding to each frame. k (x,y); for each frame of the cross-sectional image I k The geometric center of (x, y) is extracted to obtain the heartbeat frequency of the target object, and the fundamental heartbeat frequency f is extracted. c For two adjacent frames of the cross-sectional image I k (x,y) are compared to obtain the cross-sectional images I of two adjacent frames. k The translation component (Δx) of (x,y) g (k),Δy g (k)) and rotation component Δθ′; based on the translation component (Δx) g (k),Δy g (k)) and the rotation component Δθ′, for each frame of the cross-sectional image I k The (x,y) coordinates are compensated to obtain the corrected cross-sectional image I′. k (x′,y′).

[0009] As a further improvement of the present invention, the intravascular ultrasound image is a pull-back image sequence of the target vascular segment.

[0010] As a further improvement of the present invention, the cardiac fundamental frequency f c The acquisition includes: acquiring the cross-sectional image I for each frame. k The geometric center C of (x,y) k (x g ,y g ), and for each of the geometric centers C k (x g ,y g The x-axis coordinate sequence x in ) g Extraction is performed to obtain the x-axis coordinate sequence x. gSpectrum And based on the spectrum Obtain the heartbeat fundamental frequency f c .

[0011] As a further improvement of the present invention, the translation component (Δx) g (k),Δy g The acquisition of (k) includes: using filter H(f) on the cross-sectional image I of each frame. k The geometric center C of (x,y) k (x g ,y g ) Perform filtering to obtain the updated geometric center C′ k (x′ g ,y′ g ); the geometric center C k (x g ,y g ) and the updated geometric center C′ k (x′ g ,y′ g The two are compared and the positional difference between them is calculated; the positional difference is the translation component (Δx). g (k),Δy g (k)).

[0012] As a further improvement of the present invention, the filter H(f) is a comb filter, and the filter H(f) is used to filter out the heartbeat fundamental frequency f. c Including the influence of the first four harmonics, the filter H(f) is specifically as follows:

[0013]

[0014] Where k = 1, 2, ..., N is the number of image frames in the pullback sequence; n is the filter order; Δf is the passband width of the filter; and t is the harmonic order.

[0015] As a further improvement of the present invention, the order n of the filter is 3; the passband width Δf of the filter is 0.3×f c .

[0016] As a further improvement of the present invention, the acquisition of the rotation component Δθ′ includes: taking two adjacent frames of the cross-sectional image I k Registration is performed on (x, y) so that the rotated k-th frame of the cross-sectional image I k (x,y) and the cross-sectional image I of the (k-1)th frame k-1 (x,y) has the largest overlapping area, and for the k-th frame of the cross-sectional image I kThe rotation angle sequence Δθ of (x,y) is extracted; the rotation angle sequence Δθ is filtered using a comb bandpass filter 1-H(f) to extract the rotation component Δθ′, and the rotation component Δθ′ is the rotation that is only affected by the heartbeat.

[0017] As a further improvement of the present invention, the rotation component Δθ′ is expressed as: Δθ′=Δθ*(1-H(f)), where * is the convolution symbol.

[0018] As a further improvement of the present invention, the corrected cross-sectional image I′ k (x′, y′) can be represented as:

[0019]

[0020] To achieve the above-mentioned objectives, the present invention also provides an intravascular ultrasound image processing system, which can be used to execute the aforementioned intravascular ultrasound image processing method; the intravascular ultrasound image processing system includes: an image acquisition module for acquiring and storing intravascular ultrasound images of a target vascular segment; and a central processing unit for processing the intravascular ultrasound images to acquire a cross-sectional image I. k (x,y); the central processing unit is also used to base the cross-sectional image I k (x,y), for two adjacent frames of the cross-sectional image I k The translation component (Δx) of (x,y) g (k),Δy g (k)) and rotation component Δθ′, for each frame of the cross-sectional image I k The (x,y) coordinates are compensated to obtain the corrected cross-sectional image I′. k (x′,y′).

[0021] The beneficial effects of this invention are:

[0022] The intravascular ultrasound image processing method of the present invention performs frame-by-frame segmentation of the intravascular ultrasound image; and obtains the heart rate of the target object and extracts the fundamental heart rate f. c ; Compare and obtain the cross-sectional images I of two adjacent frames k The translation component (Δx) of (x,y) g (k),Δy g (k)) and rotation component Δθ′; based on the translation component (Δx) g (k),Δy g (k)) and the rotation component Δθ′, for each frame of the cross-sectional image I k The (x,y) coordinates are compensated to obtain the corrected cross-sectional image I′. k(x′,y′) is used to preserve the irregular shape of the blood vessels themselves while removing the translation and rotation between images, reducing the computational complexity of image-based heart rate extraction, and taking into account the influence of heart rate harmonics, thus making the compensation for heart rate movement more accurate. Attached Figure Description

[0023] Figure 1 This is a flowchart of the method for processing intravascular ultrasound images according to the present invention.

[0024] Figure 2 This is a schematic diagram of the motion between adjacent lumens in an intravascular ultrasound image.

[0025] Figure 3 It is the geometric center C k (x g ,y g The x-axis coordinate sequence x in ) g The periodic fluctuation chart.

[0026] Figure 4 It is the spectrum The periodic fluctuation chart.

[0027] Figure 5 It is a cross-sectional image I k The geometric center C of (x,y) k (x g ,y g )sequence.

[0028] Figure 6 This is the cross-sectional image I of the present invention. k The updated geometric center C′ is (x,y). k (x′ g ,y′ g )sequence.

[0029] Figure 7 It is a longitudinal cross-sectional image of an unprocessed intravascular ultrasound image.

[0030] Figure 8 It is a longitudinal cross-sectional image of an intravascular ultrasound image obtained by the intravascular ultrasound image processing method of the present invention. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0032] It should be noted that, in order to avoid obscuring the present invention with unnecessary details, only the structures and / or processing steps closely related to the present invention are shown in the accompanying drawings, while other details that are not closely related to the present invention are omitted.

[0033] Additionally, it should be noted that the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0034] Please see Figure 1 As shown, this invention provides a method for processing intravascular ultrasound images, which includes the following steps:

[0035] Acquire intravascular ultrasound images of the target blood vessel segment, segment the intravascular ultrasound images frame by frame, and obtain the cross-sectional image I corresponding to each frame. k (x,y);

[0036] For each frame of the cross-sectional image I k The geometric center of (x, y) is extracted to obtain the heartbeat frequency of the target object, and the fundamental heartbeat frequency f is extracted. c ;

[0037] For two adjacent frames of the cross-sectional image I k (x,y) are compared to obtain the cross-sectional images I of two adjacent frames. k The translation component (Δx) of (x,y) g (k),Δy g (k)) and rotational component Δθ′;

[0038] Based on the translation component (Δx) g (k),Δy g (k)) and the rotation component Δθ′, for each frame of the cross-sectional image I k The (x,y) coordinates are compensated to obtain the corrected cross-sectional image I′. k (x′,y′).

[0039] The following section of the instruction manual will describe in detail the methods for processing intravascular ultrasound images.

[0040] In this invention, the intravascular ultrasound images are a sequence of pulled-back images of the target vascular segment; further, the intravascular ultrasound images are segmented frame by frame to obtain the cross-sectional image I corresponding to each frame. k (x,y), where k=1,2,…,N, that is, the pull-back image sequence of the target vessel segment contains a total of N frames. In fact, during the acquisition of intravascular ultrasound images, the movement of the imaging catheter relative to the coronary artery wall caused by cardiac contraction will produce a jagged artifact in the longitudinal section of the intravascular ultrasound image, which in turn affects the visualization and quantification of the intravascular ultrasound image pull-back sequence.

[0041] Furthermore, the overall motion displacement of the coronary artery wall includes the motion component caused by the heartbeat and the geometric component caused by the irregular shape of the lumen itself. The motion component caused by the heartbeat is the main factor affecting the intravascular ultrasound image and causing the longitudinal section to produce a sawtooth artifact, which needs to be removed during the compensation process; while the geometric component caused by the irregular shape of the lumen itself is the imaging content that needs to be retained.

[0042] Please see Figure 2 As shown, the motion component caused by the heartbeat includes the relative motion between the imaging catheter and the vessel wall, and the rotational movement of the imaging catheter in the axial direction. Further, the motion component caused by the heartbeat is described as the motion of two adjacent cross-sectional images I. k Translation and rotation between the vascular lumens of (x,y).

[0043] When describing the translation and rotation between blood vessel lumens, firstly, the cross-sectional images I of each frame after segmentation are processed. k The geometric center of (x, y) is extracted to obtain the heart rate of the target object corresponding to the target blood vessel segment, and the fundamental heart rate f of the target object is obtained. c .

[0044] In this application, the fundamental frequency of the heartbeat f c The acquisition includes: acquiring the cross-sectional image I for each frame. k The geometric center C of (x,y) k (x g ,y g Specifically, the geometric center C k (x g ,y g The x-axis and y-axis coordinate sequences of the data both exhibit periodic fluctuations. Further, see [reference needed]. Figure 3 As shown, for each of the geometric centers C k (x g ,y g The x-axis coordinate sequence x in ) g Extract, further, see [link / reference] Figure 4 As shown, for the obtained x-axis coordinate sequence x g Its spectrum is obtained by performing a Fourier transform. And based on the spectrum Obtain the heartbeat fundamental frequency f c , specifically Figure 4 The area enclosed by the medium-long dashed line represents the fundamental frequency of the heartbeat, while the area enclosed by the short dashed line represents the harmonics; both the fundamental frequency and the harmonics are frequency bands that need to be filtered out.

[0045] It should be noted that this specification only considers each geometric center C. k (x g ,yg The x-axis coordinate sequence x in ) g Extract and obtain its spectrum. And based on the spectrum Obtain the heartbeat fundamental frequency f c For example, this can be illustrated by referring to an example; in other embodiments of this application, it can also be illustrated by each geometric center C. k (x g ,y g The y-axis coordinate sequence in ) g Extract and obtain its spectrum. And based on the spectrum Obtain the heartbeat fundamental frequency f c That is, the center hopping fundamental frequency f of this invention c The methods of obtaining this information are merely illustrative and should not be taken as limiting.

[0046] Furthermore, the translation component (Δx) g (k),Δy g The acquisition of (k) includes: using filter H(f) on the cross-sectional image I of each frame. k The geometric center C of (x,y) k (x g ,y g ) Perform filtering to obtain the updated geometric center C′ k (x′ g ,y′ g ); the geometric center C k (x g ,y g ) and the updated geometric center C′ k (x′ g ,y′ g The two are compared and the positional difference between them is calculated; the positional difference is the translation component (Δx). g (k),Δy g (k)).

[0047] In this invention, the geometric center C k (x g ,y g ) is a cross-sectional image I k The sequence of lumen geometric centers (x, y) is given, where k represents the geometric center of the k-th frame; filter H(f) is a comb filter used to filter out the heartbeat fundamental frequency f. cRegarding the influence of the first four harmonics, it should be noted that in the case of triangular oscillation, the Fourier series decreases at a rate of 1 / n². Therefore, the amplitude of the fifth harmonic is 1 / 25 of the main harmonic (n=1). Thus, stopping the summation at n=4 is sufficient to satisfy the filter H(f) in filtering out the harmonics. Of course, in other embodiments of this application, the order of harmonic filtering can be selected according to actual needs. The order of harmonic filtering in this invention is only exemplary and should not be limited thereto.

[0048] Furthermore, the filter H(f) is specifically as follows:

[0049]

[0050] Where k = 1, 2, ..., N is the number of image frames in the pullback sequence; n is the filter order; Δf is the filter passband width; t is the harmonic order; preferably, the filter order n is 3; the filter passband width Δf is 0.3 × f c .

[0051] In this invention, the updated geometric center C′ after filtering by filter H(f) k (x′ g ,y′ g ) is represented as:

[0052]

[0053] Here, * represents the convolution symbol.

[0054] Furthermore, the translation component (Δx) g (k),Δy g (k) is represented as:

[0055]

[0056] The acquisition of the rotation component Δθ′ includes: taking the cross-sectional images I of two adjacent frames. k Registration is performed on (x, y) so that the rotated k-th frame of the cross-sectional image I k (x,y) and the cross-sectional image I of the (k-1)th frame k-1 (x,y) has the largest overlapping area, and for the k-th frame of the cross-sectional image I k The rotation angle sequence Δθ of (x,y) is extracted; the rotation angle sequence Δθ is filtered using a comb bandpass filter 1-H(f) to extract the rotation component Δθ′, and the rotation component Δθ′ is the rotation that is only affected by the heartbeat.

[0057] Specifically, the rotation component Δθ′ is expressed as:

[0058] Δθ′=Δθ*(1-H(f)),

[0059] Here, * represents the convolution symbol.

[0060] Based on the rotation component Δθ′ and the translation component (Δx) g (k),Δy g (k) completes the cross-sectional image I for each frame. k The translation and rotational motion components of (x,y) are compensated and corrected to obtain the corrected cross-sectional image I′. k (x′,y′); further, the corrected cross-sectional image I′ k (x′, y′) can be represented as:

[0061]

[0062] See Figure 5 , Figure 6 As shown, the geometric center sequence C of the intravascular ultrasound image obtained by the intravascular ultrasound image processing method of the present invention effectively eliminates the cardiac motion artifact in the intravascular ultrasound image. Further, see [reference needed]. Figure 7 , Figure 8 As shown, the corrected intravascular ultrasound image effectively eliminates motion artifacts, significantly improving the visualization of its longitudinal cross-sectional image. Consequently, the accuracy of 3D reconstruction, volume measurement, and various derived assessments of coronary artery stenosis morphology obtained using intravascular ultrasound images is effectively improved. Based on this, compared to existing methods, this method preserves the irregular shape of the blood vessel itself, reduces the computational complexity of image-based heart rate extraction, and considers the influence of heart rate harmonics, resulting in more accurate compensation for heart rate motion.

[0063] This invention also provides an intravascular ultrasound image processing system, which can be used to execute the intravascular ultrasound image processing method of this invention; the intravascular ultrasound image processing system includes: an image acquisition module for acquiring and storing intravascular ultrasound images of a target vascular segment; and a central processing unit for processing the intravascular ultrasound images to acquire a cross-sectional image I. k (x,y); the central processing unit is also used to base the cross-sectional image I k (x,y), for two adjacent frames of the cross-sectional image I k The translation component (Δx) of (x,y) g (k),Δy g (k)) and rotation component Δθ′, for each frame of the cross-sectional image I k The (x,y) coordinates are compensated to obtain the corrected cross-sectional image I′. k (x′,y′).

[0064] It should be noted that the cross-sectional image I is obtained by processing intravascular ultrasound images. k (x,y) can also be performed outside the intravascular ultrasound image processing system. Furthermore, the intravascular ultrasound image can be segmented to obtain a cross-sectional image I. k The (x,y) method can be any segmentation method for intravascular ultrasound images in the prior art. Since the segmentation method for intravascular ultrasound images is a mature technology, it will not be described in detail in the specification of this invention.

[0065] In summary, the intravascular ultrasound image processing method of the present invention performs frame-by-frame segmentation of the intravascular ultrasound image; obtains the heart rate of the target object, and extracts the fundamental heart rate f. c ; Compare and obtain the cross-sectional images I of two adjacent frames k The translation component (Δx) of (x,y) g (k),Δy g (k)) and rotation component Δθ′; based on the translation component (Δx) g (k),Δy g (k)) and the rotation component Δθ′, for each frame of the cross-sectional image I k The (x,y) coordinates are compensated to obtain the corrected cross-sectional image I′. k (x′,y′) is used to preserve the irregular shape of the blood vessels themselves while removing the translation and rotation between images, reducing the computational complexity of image-based heart rate extraction, and taking into account the influence of heart rate harmonics, thus making the compensation for heart rate movement more accurate.

[0066] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for processing intravascular ultrasound images, characterized in that, Includes the following steps: Acquire intravascular ultrasound images of the target blood vessel segment, segment the intravascular ultrasound images frame by frame, and obtain the cross-sectional image corresponding to each frame. ; For each frame of the cross-sectional image geometric center Extraction is performed to obtain the heartbeat frequency of the target object, and the fundamental heartbeat frequency is extracted. ; The cross-sectional images of two adjacent frames Perform comparison processing to obtain the cross-sectional images of two adjacent frames. Translation components and rotational components ; Based on the translation components and the rotation component For each frame of the cross-sectional image Compensation processing is performed to obtain the corrected cross-sectional image. ; Among them, the heartbeat fundamental frequency The acquisition includes: Obtain the cross-sectional image of each frame. geometric center ), and for each of the geometric centers x-axis coordinate sequence Extraction is performed to obtain the x-axis coordinate sequence. Spectrum (f), and based on the said spectrum (f) Obtain the heart rate ; The translation component The acquisition includes: Use filters For each frame of the cross-sectional image geometric center Perform filtering processing; the filter It is a comb filter, the filter Used to filter out the heartbeat fundamental frequency Including the influence of the first four harmonics, the filter Specifically: ； Where k = 1, 2, ..., N is the number of image frames in the pullback sequence; n is the filter order; Δf is the filter passband width; and t is the harmonic order.

2. The method for processing intravascular ultrasound images according to claim 1, characterized in that, The intravascular ultrasound images are a sequence of pulled-back images of the target vascular segment.

3. The method for processing intravascular ultrasound images according to claim 1, characterized in that, The translation component The acquisition includes: Use filters For each frame of the cross-sectional image geometric center Perform filtering to obtain the updated geometric center. ; The geometric center With the updated geometric center The two are compared and the positional difference between them is calculated; the positional difference is the translation component. .

4. The method for processing intravascular ultrasound images according to claim 1, characterized in that, The filter has an order n of 3; the filter's passband width Δf is 0.3 × .

5. The method for processing intravascular ultrasound images according to claim 1, characterized in that, The rotation component The acquisition includes: The cross-sectional images of two adjacent frames Registration is performed so that the rotated k-th frame of the cross-sectional image is obtained. The cross-sectional image described in frame k-1 Having the largest overlapping area, and for the cross-sectional image of the k-th frame. rotation angle sequence Extract; Using a comb-type bandpass filter 1- For the rotation angle sequence Perform filtering to extract the rotation component. And the rotation component The rotation is affected only by the heartbeat.

6. The method for processing intravascular ultrasound images according to claim 5, characterized in that, The rotation component Represented as: ,in, This is the convolution symbol.

7. The method for processing intravascular ultrasound images according to claim 1, characterized in that, The corrected cross-sectional image Represented as: 。 8. A system for processing intravascular ultrasound images, which can be used to execute the method for processing intravascular ultrasound images according to any one of claims 1 to 7; characterized in that, The intravascular ultrasound image processing system includes: An image acquisition module, which is used to acquire and store intravascular ultrasound images of the target vascular segment; The central processing unit (CPU) is used to segment the intravascular ultrasound image to obtain a cross-sectional image. ; The central processing unit is also used to base the cross-sectional image For the cross-sectional images of two adjacent frames Translation components and rotational components For each frame of the cross-sectional image Compensation processing is performed to obtain the corrected cross-sectional image. .

Images