Motion correction method and device for medical scanning and medical imaging system

Abstract

The invention relates to a motion correction method and device for medical scanning and a medical imaging system.The motion correction method for medical scanning comprises the steps that motion model parameters are obtained; the motion model parameters represent the mapping relation between the body surface displacement and the breathing motion data of the scanning part; when the monitored object is subjected to medical scanning, a first displacement curve of the body surface of the monitored object is obtained based on the echo signals; according to the first displacement curve and the motion model parameters, determining first respiratory motion data of the scanned part of the monitored object; and performing motion correction on medical scanning imaging of the monitored object according to the first respiratory motion data. The body surface displacement curve is mapped into the breathing movement of the in-vivo scanning part, and the movement correction performance in the free breathing state can be improved. Therefore, the precision and the effect of monitoring the movement of the scanned part can be improved.

Description

Technical Field

[0001] The present application relates to the field of magnetic resonance scanning, and in particular to a motion correction method, device and medical imaging system for medical scanning. Background Art

[0002] For the magnetic resonance heart scanning scenario in the free breathing state, the physiological movement of the heart caused by breathing can be monitored to perform motion correction on the magnetic resonance scanning data, so that the image quality of the magnetic resonance heart scanning in the free breathing state can be closer to the image quality in the breath-holding state.

[0003] In the related art, the indirect monitoring of chest (abdomen) respiratory movement is often used to replace heart movement for motion correction. Usually, a breathing belt is used to monitor the respiratory movement of the chest (abdomen). Since the breathing belt needs to be tightly tied to the chest and abdomen of the monitored object, the sensing accuracy is low and it is easy to cause physical discomfort. Therefore, the accuracy and effect of monitoring the movement of scanning parts such as the heart are currently poor.

[0004] With regard to the problem of poor monitoring accuracy and effect of the movement of the scanning part in the related technology, no effective solution has been proposed so far. Summary of the invention

[0005] In this embodiment, a motion correction method, device and medical imaging system for medical scanning are provided to solve the problem of poor monitoring accuracy and effect of cardiac motion in related technologies.

[0006] In a first aspect, a motion correction method for medical scanning is provided in this embodiment, comprising:

[0007] Acquiring motion model parameters; the motion model parameters represent the mapping relationship between body surface displacement and respiratory motion data of the scanned part;

[0008] When performing a medical scan on a monitored object, obtaining a first displacement curve of a body surface of the monitored object based on an echo signal;

[0009] determining first respiratory motion data of a scanned portion of the monitored object according to the first displacement curve and the motion model parameters;

[0010] Motion correction is performed on the medical scan imaging of the monitored object according to the first respiratory motion data.

[0011] In some of the embodiments, before obtaining the motion model parameters, the method further includes:

[0012] Acquire second respiratory motion data of the scanned part of the data acquisition object, and simultaneously acquire a second displacement curve of the body surface of the data acquisition object;

[0013] The second displacement curve is fitted with the second respiratory motion data to obtain the motion model parameters.

[0014] In some embodiments, obtaining the second respiratory motion data of the scanned part of the data acquisition object includes:

[0015] Acquire scanned images of the scanned part in different imaging directions acquired during the cardiac diastole period of the data acquisition object;

[0016] The second respiratory motion data of the scanned part in different spatial positioning directions are obtained by registration according to the scanned images in different imaging directions.

[0017] In some embodiments, when performing a medical scan on a monitored object, obtaining a first displacement curve of the body surface of the monitored object based on an echo signal includes:

[0018] When performing a medical scan on a monitored object, an echo signal reflected from the body surface of the monitored object under detection of a preset transmission signal is obtained;

[0019] Extracting an echo signal whose accuracy reaches a preset condition from the echo signals to obtain an optimized echo signal;

[0020] Phase extraction and phase unwrapping processing are performed on the optimized echo signal to obtain the first displacement curve.

[0021] In some embodiments, extracting an echo signal whose accuracy reaches a preset condition from the echo signal to obtain an optimized echo signal includes:

[0022] Using the echo signal as the input of a preset optimal solution approximation algorithm, using the optimal solution approximation algorithm based on a preset objective function to update the initial optimization weight until the updated optimization weight reaches a preset iteration termination condition, and outputting the optimization weight after the iteration termination;

[0023] The optimization weight is multiplied by the echo signal to obtain an optimized echo signal.

[0024] In some of the embodiments, the objective function is used to characterize the echo energy stability after the echo signal is multiplied by the optimization weight.

[0025] In some embodiments, determining first respiratory motion data of a scanned portion of the monitored object according to the first displacement curve and the motion model parameter includes:

[0026] Determining displacement data of a scanned part of the monitored object in different spatial positioning directions according to the first displacement curve and the motion model parameters;

[0027] The displacement data is orthogonally decomposed to obtain first respiratory motion data of the scanned part of the monitored object in the slice selection direction, the phase encoding direction and the frequency encoding direction respectively.

[0028] In some embodiments, performing motion correction on the medical scan imaging of the monitored object according to the first respiratory motion data includes:

[0029] According to the first respiratory motion data in the layer selection direction, during the medical scanning process, the imaging layer position is adjusted in real time so that the imaging layer and the scanning part remain relatively stationary in the layer selection direction; and / or,

[0030] According to the first respiratory motion data in the phase encoding direction and the first respiratory motion data in the frequency encoding direction, the motion parallel to the imaging plane is corrected by phase shifting.

[0031] In a second aspect, a motion correction device for medical scanning is provided in this embodiment, comprising: an acquisition module, a curve extraction module, a motion estimation module and a motion correction module; wherein:

[0032] The acquisition module is used to acquire motion model parameters; the motion model parameters represent the mapping relationship between body surface displacement and respiratory motion data of the scanned part;

[0033] The curve extraction module is used to obtain a first displacement curve of the body surface of the monitored object based on the echo signal when performing a medical scan on the monitored object;

[0034] The motion estimation module is used to determine first respiratory motion data of a scanned part of the monitored object according to the first displacement curve and the motion model parameters;

[0035] The motion correction module is used to perform motion correction on the medical scan imaging of the monitored object according to the first respiratory motion data.

[0036] In a third aspect, a medical imaging system is provided in this embodiment, including: a medical scanning device and an echo signal detection device;

[0037] The echo signal detection device is used to project a transmission signal to the surface of the monitored object and receive an echo signal reflected back from the transmission signal;

[0038] The medical scanning device is used to execute the motion correction method for medical scanning described in the first aspect above.

[0039] In a fourth aspect, in this embodiment, a storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the motion correction method for medical scanning described in the first aspect is implemented.

[0040] Compared with the related art, the present embodiment provides a motion correction method, device and medical imaging system for medical scanning. The motion correction method for medical scanning first obtains motion model parameters; the motion model parameters characterize the mapping relationship between body surface displacement and respiratory motion data of the scanned part; then, when performing a medical scan on the monitored object, a first displacement curve of the body surface of the monitored object is obtained based on the echo signal; next, according to the first displacement curve and the motion model parameters, the first respiratory motion data of the scanned part of the monitored object is determined; finally, according to the first respiratory motion data, motion correction is performed on the medical scanning imaging of the monitored object. It maps the body surface displacement curve to the respiratory motion of the scanned part in the body, which can improve the performance of motion correction in the free breathing state. Therefore, the accuracy and effect of motion monitoring of the scanned part can be improved.

[0041] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0043] Figure 1 is a hardware structure block diagram of a terminal of the medical scanning motion correction method of this embodiment;

[0044] Figure 2 is a flow chart of the motion correction method for medical scanning of the present embodiment;

[0045] Figure 3 is a schematic diagram of radar equipment deployment in this embodiment;

[0046] Figure 4 is a schematic diagram of radar data optimization in some of the embodiments;

[0047] Figure 5 is a schematic diagram of establishing a motion model in some of the embodiments;

[0048] Figure 6 is a schematic diagram of motion correction of some embodiments;

[0049] Figure 7is a flow chart of a method for motion correction of medical scans of some embodiments;

[0050] Figure 8 is a structural block diagram of the motion correction device for medical scanning of the present embodiment;

[0051] Fig. 9 Schematic diagram of the structure of the medical imaging system of this embodiment. DETAILED DESCRIPTION

[0052] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0053] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the general meaning understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the", "these" and the like in this application do not represent quantitative restrictions, and they can be singular or plural. The terms "include", "comprise", "have" and any variants thereof involved in this application are intended to cover non-exclusive inclusions; for example, a process, method and system, product or device comprising a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether directly or indirectly. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. Usually, the character " / " indicates that the objects associated with each other are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0054] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. For example, running on a terminal, Figure 1 FIG. 1 is a block diagram of the hardware structure of a terminal of the medical scanning motion correction method of this embodiment. Figure 1 As shown, the terminal may include one or more ( Figure 1Only one is shown in the figure) processor 102 and memory 104 for storing data, wherein processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA. The above terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0055] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the motion correction method of medical scanning in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the terminal via a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0056] The transmission device 106 is used to receive or send data via a network. The above network includes a wireless network provided by the communication provider of the terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0057] In this embodiment, a method for monitoring cardiac motion is provided. Figure 2 is a flow chart of the motion correction method for medical scanning of this embodiment. Figure 2 As shown, the process includes the following steps:

[0058] Step S210, obtaining motion model parameters; the motion model parameters represent the mapping relationship between body surface displacement and respiratory motion data of the scanned part.

[0059] The motion model parameters can be pre-fitted before performing a medical scan on the scanned part of the monitored object. The motion model parameters can be various parameters in the motion model obtained by fitting the body surface displacement and the respiratory motion data of the scanned part. The above-mentioned body surface displacement can be the displacement of the human body surface in a free breathing state, detected by a signal detection device such as a millimeter wave radar, for example, the displacement of the body surface chest and abdominal cavity detected based on the millimeter wave radar. The scanned part can specifically be the heart, or other organs affected by breathing (liver, kidney, etc.). The respiratory motion data of the scanned part refers to the physiological motion data of the scanned part in a free breathing state of the human body.

[0060] Specifically, the above-mentioned motion model parameters can be fitted based on the respiratory motion data of the scanned part of a certain data acquisition object and the synchronously acquired body surface displacement data of the data acquisition object. The data acquisition object is a human body. The data acquisition object can be the same object as the monitored object, or it can be a different object. Afterwards, the motion model parameters obtained by fitting are saved in a text file. Among them, the body surface displacement and the respiratory motion data of the scanned part in different imaging directions (such as the head and foot direction, the front-back direction, and the left-right direction) can be fitted respectively to obtain the corresponding motion model parameters. At this point, the association between the body surface displacement and the actual respiratory motion of the scanned part is completed. Afterwards, when it is necessary to monitor the respiratory motion of the scanned part of the monitored object, the above-mentioned motion model parameters obtained by pre-fitting are read.

[0061] Step S220: when performing a medical scan on the monitored object, a first displacement curve of the body surface of the monitored object is obtained based on the echo signal.

[0062] Specifically, the monitored object can be subjected to medical scanning such as magnetic resonance, ultrasound scanning or positron emission tomography. The following will mainly be explained by taking cardiac magnetic resonance scanning of the monitored object as an example. The monitored object is scanned using a preset cardiac magnetic resonance sequence to obtain corresponding imaging data. At the same time, an echo signal detection device is used to project a transmission signal to the monitored object, and the echo signal reflected back from the chest and abdominal cavity of the monitored object is collected, and then the echo signal is processed to obtain a first displacement curve describing the displacement of the body surface of the monitored object. Among them, the above-mentioned echo signal detection device can be a radar device or other detection equipment, and the above-mentioned echo signal can be radar data such as 24 GHz radar data, 60 GHz radar data, 77 GHz radar data, or other types of echo signals. In particular, in order to improve the detection accuracy, a millimeter wave radar device can be used to project a millimeter wave radar to the monitored object, and the radar data reflected back from the chest and abdominal cavity of the monitored object is collected. The first displacement curve is a graphical representation of the measured small displacement changes generated by the body surface during physiological activities such as breathing or heartbeat.

[0063] Step S230: determining first respiratory motion data of the scanned part of the monitored object according to the first displacement curve and the motion model parameters.

[0064] Since the motion model parameters obtained in the above step S210 can characterize the mapping relationship between the displacement of the body surface and the respiratory motion data of the scanned part, after obtaining the first displacement curve, the respiratory motion of the scanned part can be estimated based on the above motion model parameters to obtain the first respiratory motion data corresponding to the medical scan. For example, the displacement data of the heart in the relative end-respiratory state is calculated in real time based on the motion model parameters and the first displacement curve, and then the first respiratory motion data of the heart is obtained based on the motion decomposition. The above first respiratory motion data may include motion data of the scanned part in different directions relative to the imaging level, such as motion data in the layer selection direction, the phase encoding direction, and the frequency encoding direction.

[0065] Step S240: performing motion correction on the medical scan imaging of the monitored object according to the first respiratory motion data.

[0066] The motion correction in this step may include both prospective motion correction and retrospective motion correction, wherein the prospective motion correction is to monitor the physiological motion of the scanned part caused by breathing to avoid motion artifacts, and the retrospective motion correction is to eliminate motion artifacts during digital post-processing.

[0067] Since it is impossible to directly monitor the movement of the scanned part caused by breathing from the body surface, the movement of the scanned part can be corrected by indirectly monitoring the displacement of the body surface in a free breathing state. Currently, in the related art, a breathing strap is usually used to monitor the respiratory movement of the chest or abdomen of the monitored object. Specifically, in the related art, the breathing strap needs to be tightly tied to the chest and abdomen of the monitored object. In this way, since the sensing accuracy of the breathing strap is relatively low and it causes physical discomfort to the monitored object, the measurement accuracy is low and the measurement effect is poor.

[0068] Different from the related art, in the above steps S210 to S240, non-contact detection technology is used to realize body surface displacement monitoring to replace the respiratory strap in the related art. Among them, the body surface displacement of a specific area is obtained by performing data analysis and processing on the human body area covered by the overall monitoring signal. In addition, this embodiment is based on the motion model parameters that characterize the mapping relationship between the body surface displacement and the respiratory motion data of the scanned part, which are pre-acquired, combined with the first displacement curve of the body surface, to realize the estimation of the respiratory motion data, thereby improving the performance of motion correction of medical scanning in the free breathing state.

[0069] Moreover, compared to the respiratory straps used in the related art, the acquisition of the first displacement curve of this embodiment is non-contact, and the respiratory monitoring achieved can save the cumbersome process of tying the straps to the body surface of the monitored object. In addition, compared to the respiratory straps that can only realize the respiratory movement of a local area of ​​the monitored object's body, this embodiment can monitor the respiratory movement of a larger area of ​​the body surface. Especially when using millimeter-wave radar for monitoring, since the millimeter-wave radar measurement also has a higher distance resolution, it can monitor weaker respiratory movements and avoid the sense of restraint brought to the monitored object by the respiratory straps. In addition, the overall measurement process of this embodiment can be completed automatically, and there is no need for the monitored object to get out of bed during the scanning process.

[0070] Through the above steps S210 to S240, motion model parameters are obtained; the motion model parameters characterize the mapping relationship between body surface displacement and respiratory motion data of the scanned part; when performing medical scanning on the monitored object, based on the echo signal, a first displacement curve of the body surface of the monitored object is collected; according to the first displacement curve and the motion model parameters, the first respiratory motion data of the scanned part of the monitored object is determined; according to the first respiratory motion data, motion correction is performed on the medical scanning imaging of the monitored object. It maps the body surface displacement curve to the respiratory motion of the scanned part in the body, which can improve the performance of motion correction in the free breathing state. Therefore, the accuracy and effect of motion monitoring of the scanned part can be improved.

[0071] In one embodiment, before obtaining the motion model parameters, the motion correction method may further include:

[0072] The second respiratory motion data of the scanned part of the data acquisition object is obtained, and the second displacement curve of the body surface of the data acquisition object is obtained simultaneously; the second displacement curve is fitted with the second respiratory motion data to obtain motion model parameters.

[0073] Among them, the second displacement curve describes the body surface movement, which is not directly related to the respiratory movement of the scanned part. In this regard, in this embodiment, before acquiring the medical scan image, a motion model is established in a calibration scan manner to characterize the relationship between the second displacement curve and the respiratory movement of the scanned part, so that the respiratory movement of the scanned part can be accurately estimated in the subsequent medical scan image acquisition process. The calibration scan process is a process of scanning the scanned part of the data acquisition object before acquiring the medical scan image of the monitored object, so as to establish the above-mentioned motion model in combination with the second displacement curve.

[0074] Specifically, the scanned image of the scanned part of the data acquisition object can be pre-registered to obtain the second respiratory motion data of the scanned part. The second displacement curve can be obtained based on the echo signal collected simultaneously during the calibration scan. Exemplarily, the second displacement curve can also be obtained based on millimeter wave radar collection. Specifically, while scanning the data acquisition object, the radar data scattered back by the data acquisition object under the preset millimeter wave irradiation is obtained, and then the second displacement curve is extracted therefrom.

[0075] Afterwards, a motion model is established based on the second respiratory motion data and the second displacement curve, and the body surface displacement is associated with the respiratory motion data of the scanned part. The second displacement curve is fitted with the second respiratory motion data based on fitting methods such as fractional polynomial regression, support vector machine regression, and nonlinear regression to obtain motion model parameters.

[0076] Exemplarily, based on fractional polynomial regression, the cardiac motion data and the corresponding second displacement curve are fitted to obtain the parameters of the motion model. The expression of the motion model is as follows:

[0077]

[0078]

[0079]

[0080] Among them, ΔHF, ΔAP and ΔLR correspond to the movement of the heart in the head-foot direction, front-back direction and left-right direction respectively. Radar is the second displacement curve obtained by the above solution. a, b, c are parameters used to fit the motion model, that is, motion model parameters. By using fractional polynomial regression processing, the motion model parameters between the heart movement and the second displacement curve in the head-foot direction, front-back direction and left-right direction can be solved respectively. Based on the motion model parameters, the mapping relationship between the heart movement and the chest displacement in different scanning directions can be constructed. The above motion model parameters will be retained in a text file and read and used before subsequent magnetic resonance imaging scans.

[0081] In this embodiment, by fitting the motion model between the second respiratory motion data of the scanned part and the second displacement curve, accurate mapping between the respiratory motion data of the scanned part and the body surface displacement can be achieved. This embodiment constructs a calibration scanning process, and before the formal medical scan, the motion model between the body surface displacement state and the respiratory motion of the scanned part is fitted based on the calibration scanning process, so as to improve the efficiency of estimating the respiratory motion data in the subsequent medical scanning process.

[0082] Specifically, in one embodiment, acquiring the second respiratory motion data of the scanned part of the data acquisition object may include:

[0083] The scanning images of the scanning part in different imaging directions acquired during the cardiac diastole of the data acquisition object are acquired; and the second respiratory motion data of the scanning part in different spatial positioning directions are obtained by registration according to the scanning images in different imaging directions.

[0084] For magnetic resonance scanning, the above-mentioned different imaging directions may include coronal and sagittal planes. The above-mentioned different spatial positioning directions may include head-foot direction, front-back direction, and left-right direction. Specifically, before the medical scan, a calibration scan is performed to collect multiple diastolic scan images corresponding to different imaging directions of the data acquisition object in a free breathing state. For example, the scanned part of the data acquisition object is collected in a free breathing state, corresponding to multiple diastolic scan images in the coronal and sagittal planes, respectively. Afterwards, the multiple diastolic scan images are normalized to obtain the motion data of the scanned part in the head-foot direction, front-back direction, and left-right direction, forming the second respiratory motion data.

[0085] More specifically, in the free breathing state of the data acquisition object, the scanning part of the data acquisition object is scanned in the sagittal and coronal positions respectively to obtain a set of scanned images of the diastole period, for example, 60 images. From the group of multiple scanned images, any scanned image is selected, and the image area corresponding to the scanned part is cropped out as an image template. Based on the image template, all images are subjected to normalized two-dimensional cross-correlation registration processing to obtain a set of motion data of the scanned part in the head-foot direction ΔHF, the front-back direction ΔAP, and the left-right direction ΔLK, thereby obtaining the second respiratory motion data. Among them, the expression of the normalized two-dimensional cross-correlation can be:

[0086]

[0087] Where I(x, y) is the scanned image, T is the above cropped image template, is the mean of the image template, It is the mean value of I(x, y) within the image template range.

[0088] In this embodiment, the image registration process can realize the conversion from the scanned image to the respiratory motion data under different scanning directions, so that the mapping between the respiratory motion data of the scanned part and the body surface displacement provides accurate basic data.

[0089] Additionally, in one embodiment, when performing a medical scan on a monitored object, obtaining a first displacement curve of the body surface of the monitored object based on an echo signal may specifically include:

[0090] When performing a medical scan on a monitored object, an echo signal reflected from the surface of the monitored object under a preset transmission signal detection is obtained; an echo signal with an accuracy that meets preset conditions is extracted from the echo signal to obtain an optimized echo signal; and phase extraction and phase unwrapping processing are performed on the optimized echo signal to obtain a first displacement curve.

[0091] Next, the echo signal is used as an example to illustrate the first radar data received based on the millimeter wave radar during the medical scanning stage. The first radar data can be a radar data matrix of interest obtained after the radar device transmits a signal during the medical scanning process, after the received original signal is processed and the region of interest is intercepted. Among them, the radar device can be deployed above the volume transmit coil (Volume Transmit Coil, referred to as VTC) tube and electromagnetic shielding treatment is performed. The radar device can be set in a position close to the center coil. In particular, Figure 3 FIG. 1 is a schematic diagram of radar equipment deployment in this embodiment. Figure 3 As shown, the head-end radar and the foot-end radar (radar represented by red graphics) can be deployed above the VTC tube (the area drawn by black lines in the figure), and the height above the VTC tube from the chest and abdominal cavity of the monitored object (represented by green graphics in the figure) can be 150 mm to 250 mm, and the width of the monitored object is approximately 400 mm. The radar equipment is set at an angle to the detection area. Figure 3 The left part is a forward diagram of radar deployment, and the right part is a side diagram of radar deployment. Figure 3 The radar deployment method in the figure is only an example. The specific radar equipment deployment method can be adjusted according to the needs of the actual application scenario and is not specifically limited here.

[0092] When performing millimeter wave irradiation, the radar device can transmit a frequency modulated continuous wave with the same frequency and initial phase to space through multiple transmitting antennas, and the transmission frequency is above 60 GHz. Among them, in a fast time of radar transmission, assuming that the radar device transmits a signal with power A, the working frequency of the electromagnetic wave is fc, the working bandwidth is B, and the duration of the linear frequency modulation signal is T, then at any time t, the signal s emitted by the radar is t (t) can be expressed as:

[0093]

[0094] Specifically, the received original signal is de-linearized by using a mixer. A mixer is an electronic component that can combine two signals to generate a signal with a new frequency. In this step, the radar device's transmission signal s can be de-linearized by using a mixer. t (t) and the original signal s r (t) is processed to obtain the intermediate frequency signal s b(t). The mathematical expression of the intermediate frequency signal sb(t) can be in the following form:

[0095]

[0096] Among them, σ represents the amplitude difference between the original signal and the transmitted signal, τ is the slow time, c is the speed of light, S is the linear modulation frequency, which represents the increase of frequency per unit time, R(τ) is the distance between the target and the radar, Φ RVP is the residual video phase. For near-field radar scenarios, the residual video phase may not be considered.

[0097] After obtaining the above-mentioned intermediate frequency signal, the in-phase component (In-Phase) signal and the orthogonal component (Quadrature) signal of the intermediate frequency signal are Fourier transformed to form a complex signal to distinguish signals at different distances. Afterwards, the complex signal is beamformed and static clutter filtered using a preset range-bin signal to obtain a radar data signal matrix simultaneously acquired during the medical scan. Specifically, the radar device uses an antenna array arranged in a preset form (for example, horizontally arranged or arranged in any other general form). For n receiving antennas, the radar data signal matrix U obtained above can have the following form:

[0098] U(t)=[s1(t),s2(t),...,s n (t)] (7)

[0099] Among them, s i (t) = [s i，1 (t), s i，2 (t),…,s i，M (t)] T , represents the received signal corresponding to the i-th receiving antenna at time t.

[0100] Next, from the radar data signal matrix U, the radar data within the preset range gate is intercepted as the radar data matrix of interest, so that the first radar data can be obtained. Specifically, according to the installation position of the radar equipment and the position of the monitored object in the medical scanning scene, the range gate can be selected from the received signal corresponding to each receiving antenna, and the first m data points constitute the radar data matrix of interest U. roi :

[0101]

[0102] Among them, s i，j (t) represents the signal of the jth range gate of the ith receiving antenna at time t. Thus, the first radar data is obtained.

[0103] After the first radar data is obtained, radar data with accuracy that meets a preset condition can be extracted from the first radar data as optimized radar data. Afterwards, the optimized radar data is subjected to phase information processing to obtain a first displacement curve.

[0104] It is worth mentioning that, in this embodiment, due to the influence of the physiological structure of the human body, the displacement of the body surface caused by respiratory movement varies at various positions of the body, and the difference in the displacement of the body surface will affect the quality of the received signal. Therefore, in this embodiment, the received echo signal is further processed to obtain a more accurate optimized echo signal, thereby improving the accuracy of body surface movement monitoring.

[0105] It should also be noted that the process of obtaining the second displacement curve during the calibration scan mentioned in the above embodiment is similar to the process of obtaining the first displacement curve in this embodiment, and will not be repeated here.

[0106] In particular, in one embodiment, extracting an echo signal whose accuracy meets a preset condition from the echo signal to obtain an optimized echo signal may include:

[0107] The echo signal is used as the input of the preset optimal solution approximation algorithm. The initial optimization weight is updated based on the preset objective function using the optimal solution approximation algorithm until the updated optimization weight reaches the preset iteration termination condition, and the optimization weight after the iteration termination is output; the optimization weight is multiplied by the echo signal to obtain the optimized echo signal.

[0108] The optimal solution approximation algorithm may be a nonlinear optimization algorithm or other algorithms for processing problems with nonlinear objective functions or constraints. The specific algorithm may be set according to the actual application scenario. For example, any of the following algorithms may be selected: steepest descent method, Newton method, and Gauss-Newton method.

[0109] Next, the process of obtaining the optimized echo signal in this embodiment is described by taking the nonlinear optimization algorithm combined with the millimeter wave radar as an example. roi (t), by superimposing different data weights w, different optimized radar signals y(t) = ∑w⊙U roi (t). Therefore, the initial optimization weights can be preset first, for example, using a matrix in the following form as the initial optimization weight w0:

[0110]

[0111] It is understandable that the above initial optimization weights may also be set to other forms according to the requirements of the actual application scenario, and this embodiment does not specifically limit this.

[0112] After that, starting from the initial optimization weight w0, the nonlinear optimization algorithm is used for iterative optimization. For example, the steepest descent method is used to minimize the pre-built objective function until the preset iteration termination condition is reached, and the final optimization data weight w is output. opt . The objective function is the relationship between the optimization weight and the optimized radar signal. The above iteration termination condition can be specifically when a preset number of iterations is reached, such as 300 times; or when the objective function f(w i +1), the objective function f(w i ) satisfies the preset condition, for example, |f(w i )-f(w i+1 )|<1e -9 ·(1+|f(w i )|). The specific examples of the above iteration termination conditions are for illustration only and do not constitute a specific limitation on the iteration termination conditions used in this embodiment. Based on this, the initial optimization weights can be iteratively updated by a nonlinear optimization algorithm to obtain the optimization weights corresponding to the first radar data after the iteration is terminated. After obtaining the optimization weights, each frame of data in the first radar data at the corresponding time is superimposed with the corresponding optimization weights, thereby outputting the optimized radar data.

[0113] In this embodiment, the echo signal is used as input, and the optimal solution approximation algorithm is used to iteratively solve the optimization weight, and the obtained optimization weight is used to optimize the echo signal to obtain data with higher accuracy. Therefore, this embodiment can reduce the impact of the surface displacement difference of various parts of the body on the quality of the received echo signal, thereby improving the accuracy of the displacement curve calculated subsequently.

[0114] Specifically, in one embodiment, the objective function is used to characterize the stability of the echo energy after the echo signal is multiplied by the optimization weight. The echo energy stability can be expressed as the modulus of the optimized echo signal. The objective function is an expression of the relationship between the optimization weight and the optimized echo signal. The objective function can be used to describe the modulus of the optimized echo signal, that is, the stability of the echo energy. Specifically, the objective function can have the following form:

[0115] f(w i )=E{||y(t)| p -|y0| p | q} (10)

[0116] Wherein, p represents the p-norm, q represents the q-norm; y0 represents the waveform at time 0 or a preset specific reference time. When p=1, q=2, and y0 uses a special case of statistical representation, the above objective function can have the following form:

[0117]

[0118] Furthermore, in one embodiment, the first optimization weight w opt Apply to the first radar data U roi (t), the optimized radar signal s can be output opt (t):

[0119] s opt (t) = ∑w opt ⊙U roi (t) (12)

[0120] The optimized radar data has higher accuracy than the first radar data. By performing phase extraction and phase unwrapping operations on the optimized radar data, a first displacement curve with higher accuracy can be obtained. Specifically, the phase extraction operation can be achieved through Fourier transform or phase shift method. Phase unwrapping is a technology that recovers the absolute phase that can directly reflect the physical characteristics from the measured wrapped phase (usually limited to -π to π or 0 to 2π). The phase unwrapping operation can be achieved through methods such as methods based on adjacent sampling points, cluster analysis, and two-stage planning.

[0121] Additionally, in one embodiment, based on the above step S260, determining the first respiratory motion data of the scanned part of the monitored object according to the first displacement curve and the motion model parameters may include:

[0122] According to the first displacement curve and the motion model parameters, the displacement data of the scanning part of the monitored object in different spatial positioning directions are determined; the displacement data are orthogonally decomposed to obtain the first respiratory motion data of the scanning part of the monitored object in the layer selection direction, phase encoding direction and frequency encoding direction respectively.

[0123] According to the motion model parameters fitted in the calibration scanning stage, combined with the first displacement curve, the displacement data ΔHF of the scanning part in the head and foot direction relative to the end-expiratory state can be calculated in real time. est , displacement data ΔAP in the front and rear directions est And the displacement data ΔLR in the left and right directions est By performing orthogonal decomposition on the above displacement data, the first respiratory motion data ΔSL of the scanning part in the layer selection direction, the first respiratory motion data ΔPE in the phase encoding direction, and the first respiratory motion data ΔFE in the frequency encoding direction can be obtained respectively. Among them, the movement in the layer selection direction is perpendicular to the imaging layer of the medical scan, and the movement in the phase encoding direction and the frequency encoding direction are parallel to the imaging layer of the medical scan.

[0124] In this embodiment, the first displacement curve and the motion model parameters obtained by fitting in advance are used to solve the motion data corresponding to the scanning part in the actual scanning process, so that respiratory motion data with high accuracy can be obtained.

[0125] In some embodiments, performing motion correction on a medical scan image of a monitored object according to the first respiratory motion data may specifically include:

[0126] According to the first respiratory motion data in the layer selection direction, the imaging layer position is adjusted in real time during the medical scanning process so that the imaging layer and the scanning part remain relatively stationary in the layer selection direction; and / or, according to the first respiratory motion data in the phase encoding direction and the first respiratory motion data in the frequency encoding direction, the movement parallel to the imaging layer is corrected by phase shift.

[0127] Specifically, the motion perpendicular to the imaging plane can be corrected prospectively by using plane tracking according to the first respiratory motion data of the scanning part in the layer selection direction; and / or, the motion parallel to the imaging plane can be corrected retrospectively according to the first respiratory motion data of the scanning part in the phase encoding direction and the frequency encoding direction. Among them, for magnetic resonance scanning, the imaging plane selective excitation is achieved by the combined action of the layer selection gradient magnetic field and the radio frequency pulse, and the expression is as follows:

[0128] ω=γG SL SL (13)

[0129] Where γ is the magnetic gyro ratio, G SL is the layer-selective gradient magnetic field, and SL is the spatial position in the layer-selective direction. According to the displacement data ΔSL of the scanning part in the layer-selective direction, the center frequency of the radio frequency pulse can be adjusted in real time during the magnetic resonance scanning process to change the position of the imaging layer so that the imaging layer and the movement of the heart in the layer-selective direction can be relatively still, thereby realizing the prospective correction of the movement in the layer-selective direction.

[0130] Afterwards, after the imaging data acquisition is completed, the phase shift can also be used to perform retrospective correction on the movement of the scanning part parallel to the imaging plane. Specifically, after determining the movement of the scanning part in the phase encoding direction and the frequency encoding direction, the motion correction can be performed by phase shift between Kg according to the Fourier transform theorem to achieve the above retrospective correction. Taking the movement in the frequency encoding direction as an example, it can have the following form:

[0131]

[0132] Among them, N FE is the total number of samples of a magnetic resonance signal, j is the index of the sampling point, ΔFE is the displacement of the magnetic resonance signal in the frequency encoding direction, Δφ FE(j) is the phase shift caused by ΔFE at the jth sampling point. Referring to the above formula (14), the phase encoding direction can also be phase shifted accordingly, and then the motion-corrected K-space data can be obtained. Furthermore, after the corrected K-space data is processed by the standard reconstruction process, an image with reduced motion artifacts can be obtained, thereby improving the imaging quality of the image.

[0133] When using millimeter-wave radar to monitor body surface displacement, the radar data collected by the millimeter-wave radar needs to be optimized. Figure 4 FIG. 4 is a schematic diagram of radar data optimization in some embodiments. Figure 4 As shown, first, the extracted radar data matrix of interest is input into a nonlinear programming optimizer. The nonlinear programming optimizer is a software module constructed based on a preset nonlinear optimization algorithm. The nonlinear programming optimizer is initialized with a preset initial optimization weight, a specific objective function, and optimization parameters of the nonlinear programming optimizer. The nonlinear programming optimizer begins to iteratively optimize the initial optimization weight until the preset iteration termination condition is reached, and outputs the final optimization weight obtained after the iteration termination. It can be understood that the radar data optimization process can be applied to the optimization weight process of the radar data obtained in the calibration scanning stage, and can also be applied to the optimization weight process of the radar data obtained in the medical scanning stage.

[0134] Figure 5 FIG. 4 is a schematic diagram of establishing a motion model in some of the embodiments. Figure 5 As shown, first, the multiple sagittal and coronal images of the heart acquired during the calibration scanning phase can be registered using methods such as normalized two-dimensional cross-correlation registration, thereby obtaining the second respiratory motion data of the heart in three directions (head-foot direction, front-back direction, and left-right direction). Afterwards, the second displacement curve is fitted with the motion data of the heart in three directions, thereby obtaining the motion model parameters.

[0135] Figure 6 FIG. 4 is a schematic diagram of motion correction in some embodiments. Figure 6 As shown, during the cardiac magnetic resonance scanning phase, the first displacement curve measured is input into the fitted motion model, and the heart motion caused by breathing is output, which can be specifically the displacement data of the heart in the head-foot direction, front-back direction, and left-right direction relative to the end-expiratory state. Afterwards, the above displacement data are subjected to motion decomposition to obtain the motion data of the heart in the layer selection direction, and the respiratory motion data in the phase encoding direction and the frequency encoding direction.

[0136] Next, the cardiac motion monitoring process is explained using a millimeter wave radar device as an example. Figure 7 is a flow chart of a cardiac motion monitoring method in some embodiments, such as Figure 7As shown, the cardiac motion monitoring method may include the following steps:

[0137] Step S701, during the calibration scan before the cardiac magnetic resonance sequence scan, the radar device is used to emit millimeter waves to illuminate the chest and abdomen of the monitored object, and the initial radar signal scattered back by the human body is received; wherein the radar device is deployed above the VTC tube and is subjected to electromagnetic shielding. The radar device can be set close to the center coil.

[0138] Step S702, preprocessing the initial radar signal to obtain a radar data signal matrix corresponding to the calibration scanning process after preprocessing; specifically, firstly, a mixer is used to process the transmission signal and the received initial radar signal to generate an intermediate frequency signal corresponding to the calibration scanning process. Then, the I / Q channel signal of the intermediate frequency signal corresponding to the calibration scanning process is Fourier transformed to form a complex signal corresponding to the calibration scanning process. Then, the rang-bin signal is used to perform beamforming and static clutter filtering operations on the complex signal to obtain a radar data signal matrix corresponding to the calibration scanning process.

[0139] Step S703, intercepting the radar data matrix within the preset range gate from the radar data signal matrix obtained in step S702 to obtain second radar data. It can be understood that the second radar data is the echo signal collected by the millimeter wave radar device during the calibration scan before the medical scan.

[0140] Step S704: input the second radar data into a nonlinear optimization algorithm for processing to obtain a second optimization weight; wherein, the second radar data is used as an input of the nonlinear optimization algorithm, and the initial optimization weight is iteratively optimized based on a preset objective function using the nonlinear optimization algorithm until a preset iteration termination condition is reached, and the second optimization weight after the iteration termination is output.

[0141] Step S705: multiply the second optimization weight by the second radar data to obtain second optimized radar data, and perform phase extraction and phase unwrapping operations on the second optimized radar data to obtain a second displacement curve.

[0142] Step S706, the second respiratory motion data collected before the cardiac magnetic resonance sequence scanning is fitted with the second displacement curve to obtain motion model parameters; wherein a plurality of scanned images of the heart diastole of the monitored object in the sagittal and coronal positions are collected. Based on the selected image template, the plurality of scanned images are normalized two-dimensional cross-correlation registration is performed to obtain the second respiratory motion data in different scanning directions.

[0143] Step S707, while scanning the monitored object based on the cardiac magnetic resonance sequence, obtain a first displacement curve of the monitored object based on the radar device measurement; accordingly, the calculation steps of the first displacement curve can refer to the above steps S701 to S705, and obtain the first displacement curve by processing the first radar data. The first radar data is an echo signal obtained by using a millimeter wave radar during the medical scanning process.

[0144] Step S708, determining the first respiratory motion data according to the first displacement curve and the above-mentioned motion model parameters; wherein the first respiratory motion data may specifically include the respiratory motion data of the heart in the layer selection direction, the phase encoding direction, and the frequency encoding direction. First, the displacement data of the heart in the head-foot direction, the front-back direction, and the left-right direction are calculated. Then, motion decomposition is performed according to each displacement data to obtain the respiratory motion data of the heart in the layer selection direction, the phase encoding direction, and the frequency encoding direction.

[0145] Step S709, during the cardiac magnetic resonance imaging process, the center frequency of the radio frequency pulse is adjusted in real time using the first respiratory motion data of the heart in the slice selection direction to achieve prospective correction.

[0146] Step S710, after obtaining the K-space data after the cardiac magnetic resonance scanning, phase correction is performed on the K-space data according to the first respiratory motion data of the heart in the phase encoding direction and the frequency encoding direction to achieve retrospective correction.

[0147] In the above steps S701 to S710, the radar receiving data is optimized by using a nonlinear optimization algorithm, so that a more accurate body surface displacement curve can be obtained, and then the more accurate body surface displacement curve is mapped to the movement of the heart in the body, which can improve the performance of motion correction in the free breathing state. Therefore, the accuracy and effect of heart motion monitoring can be improved.

[0148] In this embodiment, a motion correction device for medical scanning is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made are omitted. The terms "module", "unit", "subunit", etc. used below can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0149] Figure 8 80 is a structural block diagram of a motion correction device 80 for medical scanning according to the present embodiment. Figure 8 As shown, the motion correction device 80 for medical scanning includes: an acquisition module 82, a curve extraction module 84, a motion estimation module 86 and a motion correction module 88; wherein:

[0150] An acquisition module 82 is used to acquire motion model parameters; the motion model parameters characterize the mapping relationship between body surface displacement and respiratory motion data of the scanned part; a curve extraction module 84 is used to acquire a first displacement curve of the body surface of the monitored object based on the echo signal when performing a medical scan on the monitored object; a motion estimation module 86 is used to determine the first respiratory motion data of the scanned part of the monitored object based on the first displacement curve and the motion model parameters; a motion correction module 88 is used to perform motion correction on the medical scan imaging of the monitored object based on the first respiratory motion data.

[0151] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0152] In this embodiment, a medical imaging system is also provided. Fig. 9 is a schematic diagram of the structure of the medical imaging system 90 of this embodiment, please refer to Fig. 9 The medical imaging system 90 includes: a medical scanning device 92 and an echo signal detection device 94; the echo signal detection device 94 is used to project a transmission signal to the surface of the monitored object and receive an echo signal reflected back from the transmission signal; the medical scanning device 92 is used to execute the motion correction method for medical scanning provided in any of the above embodiments. The echo signal detection device 94 can be a millimeter wave radar.

[0153] In addition, in combination with the cardiac motion monitoring method provided in the above embodiments, a storage medium may be provided in this embodiment to implement the method. The storage medium stores a computer program; when the computer program is executed by a processor, any medical scan motion correction method in the above embodiments is implemented.

[0154] It should be understood that the specific embodiments described herein are only used to explain the application, rather than to limit it. Based on the embodiments provided in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of this application.

[0155] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0156] Obviously, the drawings are only some examples or embodiments of the present application. For ordinary technicians in the field, the present application can also be applied to other similar situations based on these drawings without creative work. In addition, it is understandable that although the work done in this development process may be complicated and lengthy, for ordinary technicians in the field, certain changes in design, manufacturing or production based on the technical content disclosed in this application are only conventional technical means and should not be regarded as insufficient content disclosed in this application.

[0157] The term "embodiment" in this application refers to a specific feature, structure or characteristic described in conjunction with the embodiment that can be included in at least one embodiment of the present application. The appearance of this phrase in various locations in the specification does not necessarily mean the same embodiment, nor does it mean that it is mutually exclusive with other embodiments and is independent or optional. It is clearly or implicitly understood by those of ordinary skill in the art that the embodiments described in this application can be combined with other embodiments without conflict.

[0158] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of patent protection. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the attached claims.

Claims

1. A motion correction method for medical scanning, characterized in that: include: Acquiring motion model parameters; the motion model parameters represent the mapping relationship between body surface displacement and respiratory motion data of the scanned part; When performing a medical scan on a monitored object, obtaining a first displacement curve of a body surface of the monitored object based on an echo signal; determining first respiratory motion data of a scanned portion of the monitored object according to the first displacement curve and the motion model parameters; Motion correction is performed on the medical scan imaging of the monitored object according to the first respiratory motion data.

2. The motion correction method according to claim 1, characterized in that: Before acquiring the motion model parameters, the method further includes: Acquire second respiratory motion data of the scanned part of the data acquisition object, and simultaneously acquire a second displacement curve of the body surface of the data acquisition object; The second displacement curve is fitted with the second respiratory motion data to obtain the motion model parameters.

3. The motion correction method according to claim 2, characterized in that: Acquiring second respiratory motion data of the scanned part of the data acquisition object includes: Acquire scanned images of the scanned part in different imaging directions acquired during the cardiac diastole period of the data acquisition object; The second respiratory motion data of the scanned part in different spatial positioning directions are obtained by registration according to the scanned images in different imaging directions.

4. The motion correction method according to claim 1, characterized in that: When performing a medical scan on a monitored object, obtaining a first displacement curve of the body surface of the monitored object based on an echo signal includes: When performing a medical scan on a monitored object, an echo signal reflected from the body surface of the monitored object under detection of a preset transmission signal is obtained; Extracting an echo signal whose accuracy reaches a preset condition from the echo signals to obtain an optimized echo signal; Phase extraction and phase unwrapping processing are performed on the optimized echo signal to obtain the first displacement curve.

5. The motion correction method according to claim 4, characterized in that: Extracting an echo signal whose accuracy reaches a preset condition from the echo signal to obtain an optimized echo signal includes: Using the echo signal as the input of a preset optimal solution approximation algorithm, using the optimal solution approximation algorithm based on a preset objective function to update the initial optimization weight until the updated optimization weight reaches a preset iteration termination condition, and outputting the optimization weight after the iteration termination; The optimization weight is multiplied by the echo signal to obtain an optimized echo signal.

6. The motion correction method according to claim 5, characterized in that: The objective function is used to characterize the echo energy stability after the echo signal is multiplied by the optimization weight.

7. The motion correction method according to any one of claims 1 to 6, characterized in that: Determining first respiratory motion data of a scanned part of the monitored object according to the first displacement curve and the motion model parameters includes: Determining displacement data of a scanned part of the monitored object in different spatial positioning directions according to the first displacement curve and the motion model parameters; The displacement data is orthogonally decomposed to obtain first respiratory motion data of the scanned part of the monitored object in the slice selection direction, the phase encoding direction and the frequency encoding direction respectively.

8. The motion correction method according to claim 7, characterized in that: Performing motion correction on the medical scan imaging of the monitored object according to the first respiratory motion data includes: According to the first respiratory motion data in the layer selection direction, during the medical scanning process, the imaging layer position is adjusted in real time so that the imaging layer and the scanning part remain relatively stationary in the layer selection direction; and / or, According to the first respiratory motion data in the phase encoding direction and the first respiratory motion data in the frequency encoding direction, the motion parallel to the imaging plane is corrected by phase shifting.

9. A motion correction device for medical scanning, characterized in that: include: Acquisition module, curve extraction module, motion estimation module and motion correction module; wherein: The acquisition module is used to acquire motion model parameters; the motion model parameters represent the mapping relationship between body surface displacement and respiratory motion data of the scanned part; The curve extraction module is used to obtain a first displacement curve of the body surface of the monitored object based on the echo signal when performing a medical scan on the monitored object; The motion estimation module is used to determine first respiratory motion data of a scanned part of the monitored object according to the first displacement curve and the motion model parameters; The motion correction module is used to perform motion correction on the medical scan imaging of the monitored object according to the first respiratory motion data.

10. A medical imaging system, characterized in that: include: Medical scanning equipment and echo signal detection equipment; The echo signal detection device is used to project a transmission signal to the surface of the monitored object and receive an echo signal reflected back from the transmission signal; The medical scanning device is used to perform the motion correction method for medical scanning according to any one of claims 1 to 8.

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