Mobile C-shaped arm image data acquisition method and system based on double-ring structure

Abstract

The invention relates to the technical field of image data acquisition, and provides a double-ring structure-based mobile C-shaped arm image data acquisition method, which comprises the following steps of: S1, constructing a double-ring mobile C-shaped arm structure; s2, synchronous motion control is carried out, and synchronous same-direction motion of a sliding arm along a compensation C ring and synchronous same-direction motion of a load C ring along the sliding arm are achieved through belt transmission and gear transmission; s3, multi-mode exposure collection is adopted in the data collection process, the angle of a C ring is adjusted through man-machine interaction, perspective or photography mode exposure is executed at a fixed angle, or three-dimensional mode exposure is executed by continuous exposure at a set frame rate in the movement process to obtain multi-view image data; and S4, carrying out image calibration and three-dimensional reconstruction, calibrating an image amplification error by using an optical range finder, and carrying out three-dimensional reconstruction through a sparse representation algorithm based on multi-view image data. On the premise that the intervention opening requirement of the operating bed is guaranteed, the image chain reciprocates around a patient at a large angle, and richer multi-view image data can be collected.

Description

Technical Field

[0001] The present invention relates to the technical field of image data acquisition, and in particular to a method and system for acquiring image data of a mobile C-arm based on a double-ring structure. Background Art

[0002] Mobile C-arm X-ray machines, a key type of medical imaging equipment, are widely used for real-time imaging during surgery. Their core function is to rotate around the patient's screening area using a C-arm, equipped with an imaging chain (including image acquisition equipment and X-ray transmitters), to acquire multi-view imaging data. This supports disease diagnosis, surgical navigation, and 3D image reconstruction, playing an irreplaceable role in orthopedic reduction and interventional procedures.

[0003] Currently, if Figure 1 As shown in the figure, commonly used mobile C-arm X-ray machines on the market use a single C-ring structure to carry the imaging chain: the patient is positioned at the center of the C-arm, which carries the detector and X-ray tube assembly. Theoretically, the C-arm can rotate and reciprocate around the screening area to capture multi-view images. However, in practice, due to structural limitations, it has the following significant technical shortcomings:

[0004] (1) The rotation angle is limited and the viewing angle coverage is insufficient

[0005] To accommodate interventional needs on the operating table, the device requires ample opening space. This single C-ring structure compromises opening size and rotation angle. Due to structural design limitations, the C-ring's range of rotation around the patient is limited, preventing it from fully covering the full dimensional space of the patient's screening area. This directly results in limited imaging viewing angles. For complex anatomical structures or lesions, it's difficult to acquire comprehensive, accurate, multi-view data, increasing the risk of missed diagnoses and compromising the accuracy of subsequent diagnosis and 3D reconstruction.

[0006] (2) Check process redundancy and low operational efficiency

[0007] Due to insufficient visual coverage, existing systems often require moving the C-arm or adjusting the patient's position to capture additional images from specific angles. This not only prolongs surgical examination time and increases the complexity of medical procedures, but can also disrupt the surgical process due to frequent movement of the device. Even changes in patient position can affect the continuity and consistency of image acquisition, reducing surgical efficiency and safety. Summary of the Invention

[0008] To address the above-mentioned issues, the present invention aims to provide a method and system for acquiring image data from a mobile C-arm based on a dual-ring structure. The dual-ring structure comprises a compensation C-ring and a load C-ring. The compensation C-ring is fixed to the equipment frame, and a sliding arm can slide back and forth along the compensation C-ring. The load C-ring carries the image acquisition device and X-ray emission device and can slide back and forth along the sliding arm, with the compensation C-ring and the load C-ring maintaining their centers of circle coincident. Through the dual-ring synchronous motion mechanism, the movement of the sliding arm along the compensation C-ring and the movement of the load C-ring along the sliding arm are coordinated. While ensuring sufficient opening for intervention on the operating table, this solution overcomes the angular limitations of a single-ring structure and enables large-angle reciprocating motion of the imaging chain around the patient's screening area. This solution significantly expands the C-ring's rotational angle range around the patient, allowing for the acquisition of richer multi-view imaging data, providing sufficient data support for accurate diagnosis and high-quality three-dimensional reconstruction. It also avoids the need for additional equipment or patient movement due to insufficient angles, optimizes the surgical auxiliary examination process, and improves medical efficiency and the value of imaging diagnosis.

[0009] The above-mentioned object of the present invention is achieved through the following technical solutions:

[0010] A method for acquiring image data of a mobile C-arm based on a dual-ring structure comprises the following steps:

[0011] S1: Build a dual-ring mobile C-arm structure, which includes a compensation C-ring, a sliding arm, and a load C-ring. The two C-rings move synchronously to enable the imaging chain to reciprocate around the patient at a large angle.

[0012] S2: Performing synchronous motion control, through the ring motion power system, belt drive and gear drive to achieve synchronous and unidirectional movement of the sliding arm along the compensation C-ring and the load C-ring along the sliding arm, so that the imaging chain reciprocates around the patient;

[0013] S3: Multi-mode exposure acquisition is used during data acquisition. The C-ring angle is adjusted through human-computer interaction to perform perspective or photographic mode exposure at a fixed angle, or to perform 3D mode exposure at a set frame rate during motion to obtain multi-view image data.

[0014] S4: Perform image calibration and 3D reconstruction. Use an optical rangefinder to calibrate the image magnification error, and perform 3D reconstruction based on multi-view image data using a sparse representation algorithm.

[0015] Furthermore, in step S1, the dual-ring mobile C-arm structure is constructed, specifically:

[0016] By arranging the load C-ring, the sliding arm, and the compensation C-ring, the imaging chain can reciprocate around the patient at a large angle while taking into account a larger device opening, thereby enabling the dual-ring mobile C-arm structure to obtain imaging data from more viewing angles of the patient;

[0017] The compensation C-ring is fixed on the equipment frame, the slide arm reciprocates along the compensation C-ring, and the load C-ring carries the image acquisition equipment and the X-ray arena assembly and reciprocates along the slide arm. At the same time, the compensation C-ring and the load C-ring have the same center.

[0018] Furthermore, in step S2, synchronous motion control is performed. The ring motion power system is used to achieve synchronous and unidirectional motion of the slide arm along the compensation C-ring and the load C-ring along the slide arm via belt drive and gear drive, so that the imaging chain reciprocates around the patient. Specifically,

[0019] The ring motion power system is arranged in the sliding arm and is driven by a single motor. Through belt transmission and gear transmission, the sliding arm and the load C ring are synchronously moved in the same direction along the sliding arm, so that the imaging chain reciprocates around the patient.

[0020] Adopting adaptive PID control algorithm, the motor output torque is dynamically adjusted, and the exposure angle is accurately calculated by integrating the transmission gear ratio, the arc radius of the load C ring and the compensation C ring, and the motor speed;

[0021] High-precision servo drive and the physical electrical signal of the driver's internal position are used as direct exposure drive to avoid communication transmission delays and achieve adjustable exposure angle and precise control of angle in 3D mode.

[0022] Furthermore, the exposure angle is accurately calculated by integrating the transmission gear ratio, the arc radius of the load C-ring and the compensation C-ring, and the motor speed, specifically using the following formula:

[0023]

[0024] in, is the exposure angle, Q1 is the load C-ring drive transmission gear ratio, Q2 is the compensation C-ring drive transmission gear ratio, R1 is the load C-ring arc radius, R2 is the compensation C-ring arc radius, and ΔX is the rotation displacement of the drive motor.

[0025] Furthermore, in step S3, multi-mode exposure acquisition is used during the data acquisition process, which also includes providing users with real-time feedback control during the exposure process in perspective and 3D modes, dynamically adjusting exposure parameters based on image grayscale and noise, and the device is equipped with AEC control to achieve automatic exposure control in photography mode, specifically:

[0026] In fluoroscopic or 3D mode, users can select automatic intensity control modes of high, medium, and low grayscale. During the first exposure, the system will issue the appropriate X-ray parameters in the database based on the patient's information, including weight, height, and body part. Later, the system will make real-time adjustments to the X-ray parameters based on the previous image grayscale.

[0027] In photography mode, users can choose automatic control modes of high, medium and low dose intensities. The system will issue matching radiation parameters in the database based on the patient's information including weight, height and body part. During exposure, the AEC device will detect the radiation dose in real time, and interrupt the exposure when the dose reaches the preset value.

[0028] Furthermore, in step S4, the image magnification error is calibrated using an optical rangefinder, specifically:

[0029] The detector end is equipped with the optical rangefinder, which measures the distance between the inspected object and the detector in real time to correct the image distance measurement value. According to the distance from the inspection part to the optical measurement point of the optical rangefinder and the position distance from the optical rangefinder to the detector, the position distance of the inspection part from the detector can be calculated, thereby effectively calibrating the image measurement to solve the problem of image magnification. Specifically, the following formula is used:

[0030]

[0031] Wherein, SID is the distance between the ray source and the detector surface, OID is the distance between the inspection site on the human body surface and the detector surface, x is the length distance measured by the image, and Δx is the actual length distance.

[0032] Furthermore, in step S4, 3D reconstruction is performed based on the multi-view image data using a sparse representation algorithm, specifically:

[0033] The feature dictionary is constructed, and the image processing method based on feature learning in low-dose CT is combined to construct an over-complete feature dictionary D using sample image data, where D = {d i ∈R M |||d i ||2=1,1≤i≤M},d i is the characteristic basis signal, M is the number of characteristic basis signals and M>N, N is the dimension of the signal to be represented;

[0034] Perform signal sparse coding, for the signal to be represented y∈R extracted from the multi-view image N , which is expressed as the characteristic basis signal d i The linear combination y=D*a, and the sparse representation coefficient a is solved by the sparse coding algorithm, and the solution model satisfies:

[0035]

[0036] Among them, ||α||0 is the L0 pseudo-norm, which is used to constrain the sparsity of coefficient a, D is the feature dictionary, and y represents the signal to be represented;

[0037] Perform three-dimensional image reconstruction based on the sparse representation coefficient a obtained by linear combination of characteristic basis signals d i Restore the three-dimensional features of multi-view images and ultimately generate high-precision three-dimensional images of the patient's screening area.

[0038] A mobile C-arm image data acquisition system based on a dual-loop structure for executing the above-mentioned mobile C-arm image data acquisition method based on a dual-loop structure comprises:

[0039] A dual-ring structure building module is used to build a dual-ring mobile C-arm structure. The dual-ring mobile C-arm structure includes a compensation C-ring, a sliding arm, and a load C-ring. The two C-rings move synchronously to enable the imaging chain to reciprocate around the patient at a large angle.

[0040] A synchronous motion control module is used to perform synchronous motion control, and realizes synchronous and unidirectional motion of the slide arm along the compensation C-ring and the load C-ring along the slide arm through a ring motion power system via belt drive and gear drive, so that the imaging chain reciprocates around the patient;

[0041] The multi-mode exposure acquisition module is used to acquire multi-mode exposure during data acquisition. The C-ring angle can be adjusted through human-computer interaction to perform perspective or photographic mode exposure at a fixed angle, or to perform 3D mode exposure at a set frame rate during motion to acquire multi-view image data.

[0042] The image calibration and 3D reconstruction module is used to perform image calibration and 3D reconstruction. It uses an optical rangefinder to calibrate the image magnification error and performs 3D reconstruction based on multi-view image data through a sparse representation algorithm.

[0043] A computer device includes a memory and one or more processors, wherein the memory stores computer code, and when the computer code is executed by the one or more processors, the one or more processors execute the above method.

[0044] A computer-readable storage medium stores computer code. When the computer code is executed, the above method is performed.

[0045] Compared with the prior art, the present invention has at least one of the following beneficial effects:

[0046] (1) Image acquisition range and viewing angle expansion: The dual-ring collaborative structure of the compensation C-ring, sliding arm, and load C-ring is adopted to break through the angle limitation of the single-ring structure. Under the premise of ensuring the intervention opening requirements of the operating table, the imaging chain can move back and forth around the patient at a large angle, which can collect richer multi-view imaging data, provide sufficient data support for accurate diagnosis and high-quality three-dimensional reconstruction, and make up for the defect of insufficient viewing angle coverage of traditional equipment.

[0047] (2) Improved motion control accuracy: With the help of a synchronous motion mechanism of single motor drive, belt drive and gear drive, combined with an adaptive PID control algorithm to dynamically adjust the motor output torque, the transmission parameters are integrated to accurately calculate the exposure angle, and high-precision servo drive and physical electrical signals are used to directly trigger exposure, avoiding communication delays. Flexible adjustment and precise control of the exposure angle in three-dimensional mode (angle error is controllable) are achieved to ensure the accuracy and consistency of image acquisition.

[0048] (3) Image quality and calibration optimization: Execute real-time exposure feedback. In perspective and 3D modes, dynamically adjust exposure parameters based on image grayscale and noise. The photography mode is automatically adjusted in combination with AEC control to adapt to the needs of different patient sizes and body parts, optimize radiation parameters, and ensure image quality while reasonably controlling radiation dose. Perform magnification error calibration, use an optical rangefinder to measure distance in real time, and accurately correct image measurement values through formulas to solve the measurement deviation problem caused by image magnification and improve the clinical reference value of imaging data.

[0049] (4) Enhanced 3D reconstruction: Based on a sparse representation algorithm, high-precision 3D images are generated by constructing an overcomplete feature dictionary, sparse coding, and 3D feature restoration. Combined with low-dose CT feature learning, while ensuring image quality, multi-view data is effectively utilized to improve reconstruction accuracy, providing more intuitive and accurate 3D information for disease diagnosis and surgical planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a structural diagram of a mobile C-arm X-ray machine in the prior art;

[0051] Figure 2 This is an overall flow chart of the method for acquiring image data of a mobile C-arm based on a dual-loop structure according to the present invention;

[0052] Figure 3 It is a side view schematic diagram of the device structure of the present invention;

[0053] Figure 4 This is a schematic diagram of the motion effect of the device of the present invention;

[0054] Figure 5 This is a functional block diagram of the device of the present invention;

[0055] Figure 6This is a schematic diagram of the perspective / three-dimensional exposure principle of the present invention;

[0056] Figure 7 This is a schematic diagram of the exposure principle of the photographic mode of the present invention;

[0057] Figure 8 Schematic diagram of the device of the present invention emitting a cone beam of rays;

[0058] Figure 9 A sparse representation process diagram of the present invention;

[0059] Figure 10 This is the overall structural diagram of the mobile C-arm image data acquisition system based on the dual-ring structure of the present invention. DETAILED DESCRIPTION

[0060] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0061] Those skilled in the art will appreciate that, unless otherwise stated, the singular forms "a," "an," "said," and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the stated features, integers, steps, operations, elements, and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0062] First embodiment

[0063] like Figure 2 As shown, this embodiment provides a method for acquiring image data of a mobile C-arm based on a dual-ring structure, comprising the following steps:

[0064] S1: Build a dual-ring mobile C-arm structure, which includes a compensation C-ring, a sliding arm, and a load C-ring. The two C-rings move synchronously to enable the imaging chain to reciprocate around the patient at a large angle.

[0065] In this embodiment, in step S1, the dual-ring mobile C-arm structure is constructed, specifically:

[0066] By setting the load C-ring, the sliding arm and the compensation C-ring, the imaging chain can reciprocate around the patient at a large angle while taking into account the larger device opening, so that the dual-ring mobile C-arm structure can obtain imaging data from more viewing angles of the patient, such as Figure 3 shown.

[0067] The compensation C-ring is fixed on the equipment frame, the slide arm reciprocates along the compensation C-ring, and the load C-ring carries the image acquisition equipment and the X-ray arena assembly and reciprocates along the slide arm. At the same time, the compensation C-ring and the load C-ring have the same center.

[0068] When the movement starts, it is synchronized: the slide moves along the compensation C slide, and the load C ring moves along the slide. The movement effect is as follows Figure 4 During the actual examination, the camera can be adjusted to a fixed angle through human-computer interaction to perform perspective or photography operations. It can also be used to continuously shoot multiple perspectives at a certain frame rate while moving around the patient, obtaining multi-perspective images of the patient for 3D reconstruction.

[0069] S2: Perform synchronous motion control, and realize synchronous and unidirectional motion of the sliding arm along the compensation C-ring and the load C-ring along the sliding arm through the ring motion power system via belt drive and gear drive, so that the imaging chain reciprocates around the patient.

[0070] In this embodiment, step S2 is specifically as follows:

[0071] The ring motion power system is arranged in the sliding arm and is driven by a single motor. Through belt transmission and gear transmission, the sliding arm and the load C ring are synchronously moved in the same direction along the sliding arm, so that the imaging chain reciprocates around the patient.

[0072] Adopting adaptive PID control algorithm, the motor output torque is dynamically adjusted, and the exposure angle is accurately calculated by integrating the transmission gear ratio, the arc radius of the load C ring and the compensation C ring, and the motor speed;

[0073] High-precision servo drive and the physical electrical signal of the driver's internal position are used as direct exposure drive to avoid communication transmission delays and achieve adjustable exposure angle and precise control of angle in 3D mode.

[0074] The exposure angle is accurately calculated by integrating the transmission gear ratio, the arc radius of the load C ring and the compensation C ring, and the motor speed. Specifically, the following formula is used:

[0075]

[0076] in, is the exposure angle, Q1 is the load C-ring drive transmission gear ratio, Q2 is the compensation C-ring drive transmission gear ratio, R1 is the load C-ring arc radius, R2 is the compensation C-ring arc radius, and ΔX is the rotation displacement of the drive motor.

[0077] S3: Multi-mode exposure acquisition is used during data acquisition. The C-ring angle is adjusted through human-computer interaction to perform perspective or photographic mode exposure at a fixed angle, or to perform 3D mode exposure at a set frame rate during motion to obtain multi-view image data.

[0078] like Figure 5 The figure shows the complete process logic of mobile C-arm image data acquisition and processing based on a dual-loop structure. Starting from human-computer interaction, after the user completes the command input through the operation interface, the mode selection phase is entered. This phase sets three core working paths: photography mode, fluoroscopy mode, and 3D mode according to the clinical image acquisition requirements:

[0079] Photography mode: Focuses on static, precise image acquisition scenarios. The C-ring angle is first adjusted through the mechanical control module, the imaging chain (including the detector and X-ray tube) is positioned to the target position, and a single exposure is triggered. The radiation attenuation data collected by the detector is used to generate a single high-resolution static image, meeting requirements such as fracture reduction confirmation and internal fixation device morphology assessment.

[0080] Fluoroscopic mode: For dynamic observation scenarios, it also uses C-ring angle adjustment as a pre-step. Based on a continuous exposure mechanism, it triggers radiation emission and detection multiple times at preset time intervals (e.g., 5-30 frames / second), continuously capturing multi-frame dynamic image sequences. This can present dynamic processes such as the movement trajectory of surgical instruments and the flow direction of contrast agents in real time, assisting doctors in monitoring interventional procedures.

[0081] 3D mode: To achieve 3D image reconstruction design, different from the "static angle acquisition" of the first two modes, "motion-exposure collaborative control" is introduced: driven by the dual-ring synchronous motion mechanism, the C-ring reciprocates along the collaborative trajectory of the compensation C-ring and the load C-ring, and at the same time triggers exposure at a set frame rate (such as 0.5 / frame-1° / frame interval) to collect multiple image data from different perspectives; these multi-perspective images are aggregated through the transmission link and input into the 3D reconstruction software. Through sparse representation algorithms, feature dictionary matching and other technologies, a 3D visualization model of the screening area is reconstructed, providing a three-dimensional basis for complex anatomical structure analysis and preoperative planning.

[0082] The three modes are based on the logical main line of "human-computer interaction-mode adaptation-mechanical movement-image acquisition-data processing", covering the complete process from clinical demand input to three-dimensional image output. Relying on the motion advantages of the dual-ring structure, it breaks through the viewing angle limitations of traditional single-ring C-arms and supports precise diagnosis and complex surgical scenarios.

[0083] Furthermore, in step S3, multi-mode exposure acquisition is used during the data acquisition process, which also includes providing users with real-time feedback control during the exposure process in perspective and 3D modes, dynamically adjusting exposure parameters based on image grayscale and noise, and the device is equipped with AEC control to achieve automatic exposure control in photography mode, specifically:

[0084] like Figure 6 As shown, in fluoroscopic or 3D mode, users can select high, medium, and low grayscale automatic intensity control modes. During the first exposure, the system will issue the corresponding radiation parameters in the database based on the patient's information, including weight, height, and body part. Later, the radiation will be adjusted in real time based on the grayscale of the previous image.

[0085] like Figure 7 As shown, in photography mode, users can choose automatic control modes of high, medium and low dose intensities. The system will issue matching radiation parameters in the database based on the patient's information including weight, height and body part. During exposure, the AEC device detects the radiation dose in real time, and interrupts the exposure when the dose reaches the preset value.

[0086] S4: Perform image calibration and 3D reconstruction. Use an optical rangefinder to calibrate the image magnification error, and perform 3D reconstruction based on multi-view image data using a sparse representation algorithm.

[0087] In this embodiment, in step S4, the image magnification error is calibrated using an optical rangefinder, specifically:

[0088] The rays emitted by the device are cone beams, such as Figure 8 As mentioned above, the detected object may not be closely attached to the detector surface of the device or in a fixed space within the detection area, which may cause the image to be magnified, and the magnification ratio is uncertain, resulting in a large error in the image distance measurement.

[0089] The detector end is equipped with the optical rangefinder, which measures the distance between the inspected object and the detector in real time to correct the image distance measurement value. According to the distance from the inspection part to the optical measurement point of the optical rangefinder and the position distance from the optical rangefinder to the detector, the position distance of the inspection part from the detector can be calculated, thereby effectively calibrating the image measurement to solve the problem of image magnification. Specifically, the following formula is used:

[0090]

[0091] Wherein, SID is the distance between the ray source and the detector surface, OID is the distance between the inspection site on the human body surface and the detector surface, x is the length distance measured by the image, and Δx is the actual length distance.

[0092] Furthermore, in step S4, 3D reconstruction is performed based on the multi-view image data using a sparse representation algorithm, specifically:

[0093] To achieve clearer images, the imaging algorithm combines feature-learning-based image processing methods from low-dose CT. By learning from sample data, a feature dictionary is constructed and the signal is represented using feature fields. Sparse coding algorithms can be used to solve the sparse representation of the constructed dictionary and the signal to be represented.

[0094] The feature dictionary is constructed, and the image processing method based on feature learning in low-dose CT is combined to construct an over-complete feature dictionary D using sample image data, where D = {d i ∈R M |||d i ||2=1,1≤i≤M},d i is the characteristic basis signal, M is the number of characteristic basis signals and M>N, N is the dimension of the signal to be represented;

[0095] Perform signal sparse coding, for the signal to be represented y∈R extracted from the multi-view image N , which is expressed as the characteristic basis signal d i The linear combination y=D*a, and the sparse representation coefficient a is solved by the sparse coding algorithm, and the solution model satisfies:

[0096]

[0097] Among them, ||a||0 is the L0 pseudo-norm, which is used to constrain the sparsity of coefficient a, D is the feature dictionary, and y represents the signal to be represented. The sparse representation process is as follows Figure 9 shown.

[0098] Perform three-dimensional image reconstruction based on the sparse representation coefficient a obtained by linear combination of characteristic basis signals d i Restore the three-dimensional features of multi-view images and ultimately generate high-precision three-dimensional images of the patient's screening area.

[0099] Second embodiment

[0100] like Figure 10 As shown, this embodiment provides a mobile C-arm image data acquisition system based on a dual-ring structure for executing the mobile C-arm image data acquisition method based on a dual-ring structure as in the first embodiment, comprising:

[0101] A dual-ring structure building module 1 is used to build a dual-ring mobile C-arm structure. The dual-ring mobile C-arm structure includes a compensation C-ring, a sliding arm, and a load C-ring. The two C-rings move synchronously to enable the imaging chain to reciprocate around the patient at a large angle.

[0102] Synchronous motion control module 2, used for performing synchronous motion control, using a ring motion power system, belt drive and gear drive to achieve synchronous and unidirectional motion of the slide arm along the compensation C-ring and the load C-ring along the slide arm, so that the imaging chain reciprocates around the patient;

[0103] Multi-mode exposure acquisition module 3 is used to acquire multi-mode exposure during data acquisition. The C-ring angle is adjusted through human-computer interaction to perform perspective or photographic mode exposure at a fixed angle, or to perform 3D mode exposure at a set frame rate during motion to acquire multi-view image data.

[0104] The image calibration and 3D reconstruction module 4 is used to perform image calibration and 3D reconstruction, use an optical rangefinder to calibrate the image magnification error, and perform 3D reconstruction based on multi-view image data using a sparse representation algorithm.

[0105] A computer-readable storage medium stores computer code. When the computer code is executed, the above-described method is performed. A person skilled in the art will appreciate that all or part of the steps in the various methods of the above-described embodiments can be performed by a program instructing related hardware. The program can be stored in a computer-readable storage medium. The storage medium may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0106] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiment. All technical solutions based on the concept of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should also be considered within the scope of protection of the present invention.

[0107] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0108] It should be noted that the above embodiments can be freely combined as needed. The above description is only a preferred embodiment of the present invention. It should be pointed out that those skilled in the art can make several improvements and modifications without departing from the principles of the present invention, and such improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for acquiring image data from a mobile C-arm based on a dual-ring structure, characterized in that: The following steps are involved: S1: Build a dual-ring mobile C-arm structure, which includes a compensation C-ring, a sliding arm, and a load C-ring. The two C-rings move synchronously to enable the imaging chain to reciprocate around the patient at a large angle. S2: Performing synchronous motion control, through the ring motion power system, belt drive and gear drive to achieve synchronous and unidirectional movement of the sliding arm along the compensation C-ring and the load C-ring along the sliding arm, so that the imaging chain reciprocates around the patient; S3: Multi-mode exposure acquisition is used during data acquisition. The C-ring angle is adjusted through human-computer interaction to perform perspective or photographic mode exposure at a fixed angle, or to perform 3D mode exposure at a set frame rate during motion to obtain multi-view image data. S4: Perform image calibration and 3D reconstruction. Use an optical rangefinder to calibrate the image magnification error, and perform 3D reconstruction based on multi-view image data using a sparse representation algorithm.

2. The method for acquiring mobile C-arm image data based on a dual-ring structure according to claim 1, characterized in that: In step S1, the dual-ring mobile C-arm structure is constructed, specifically: By arranging the load C-ring, the sliding arm, and the compensation C-ring, the imaging chain can reciprocate around the patient at a large angle while taking into account a larger device opening, thereby enabling the dual-ring mobile C-arm structure to obtain imaging data from more viewing angles of the patient; The compensation C-ring is fixed on the equipment frame, the slide arm reciprocates along the compensation C-ring, and the load C-ring carries the image acquisition equipment and the X-ray arena assembly and reciprocates along the slide arm. At the same time, the compensation C-ring and the load C-ring have the same center.

3. The method for acquiring mobile C-arm image data based on a dual-ring structure according to claim 1, characterized in that: In step S2, synchronous motion control is performed. The ring motion power system is used to achieve synchronous and unidirectional motion of the slide arm along the compensation C-ring and the load C-ring along the slide arm via belt drive and gear drive, so that the imaging chain reciprocates around the patient. Specifically, The ring motion power system is arranged in the sliding arm and is driven by a single motor. Through belt transmission and gear transmission, the sliding arm and the load C ring are synchronously moved in the same direction along the sliding arm, so that the imaging chain reciprocates around the patient. Adopting adaptive PID control algorithm, the motor output torque is dynamically adjusted, and the exposure angle is accurately calculated by integrating the transmission gear ratio, the arc radius of the load C ring and the compensation C ring, and the motor speed; High-precision servo drive and the physical electrical signal of the driver's internal position are used as direct exposure drive to avoid communication transmission delays and achieve adjustable exposure angle and precise control of angle in 3D mode.

4. The method for acquiring mobile C-arm image data based on a dual-ring structure according to claim 3, characterized in that: The exposure angle is accurately calculated by integrating the transmission gear ratio, the arc radius of the load C ring and the compensation C ring, and the motor speed. Specifically, the following formula is used: in, is the exposure angle, Q1 is the load C-ring drive transmission gear ratio, Q2 is the compensation C-ring drive transmission gear ratio, R1 is the load C-ring arc radius, R2 is the compensation C-ring arc radius, and ΔX is the rotation displacement of the drive motor.

5. The method for acquiring mobile C-arm image data based on a dual-ring structure according to claim 1, characterized in that: In step S3, multi-mode exposure acquisition is used during the data acquisition process. This also includes providing users with real-time feedback control during the exposure process in perspective and 3D modes, dynamically adjusting exposure parameters based on image grayscale and noise. At the same time, the device is equipped with AEC control to achieve automatic exposure control in photography mode. Specifically: In fluoroscopic or 3D mode, users can select automatic intensity control modes of high, medium, and low grayscale. During the first exposure, the system will issue the appropriate X-ray parameters in the database based on the patient's information, including weight, height, and body part. Later, the system will make real-time adjustments to the X-ray parameters based on the previous image grayscale. In photography mode, users can choose automatic control modes of high, medium and low dose intensities. The system will issue matching radiation parameters in the database based on the patient's information including weight, height and body part. During exposure, the AEC device will detect the radiation dose in real time, and interrupt the exposure when the dose reaches the preset value.

6. The method for acquiring mobile C-arm image data based on a dual-ring structure according to claim 1, characterized in that: In step S4, the image magnification error is calibrated using an optical rangefinder, specifically: The detector end is equipped with the optical rangefinder, which measures the distance between the inspected object and the detector in real time to correct the image distance measurement value. According to the distance from the inspection part to the optical measurement point of the optical rangefinder and the position distance from the optical rangefinder to the detector, the position distance of the inspection part from the detector can be calculated, thereby effectively calibrating the image measurement to solve the problem of image magnification. Specifically, the following formula is used: Wherein, SID is the distance between the ray source and the detector surface, OID is the distance between the inspection site on the human body surface and the detector surface, x is the length distance measured by the image, and Δx is the actual length distance.

7. The method for acquiring mobile C-arm image data based on a dual-ring structure according to claim 1, characterized in that: In step S4, 3D reconstruction is performed based on the multi-view image data using a sparse representation algorithm, specifically: The feature dictionary is constructed, and the image processing method based on feature learning in low-dose CT is combined to construct an over-complete feature dictionary D using sample image data, where D = {d i ∈R M |||d i ||2=1,1≤i≤M},d i is the characteristic basis signal, M is the number of characteristic basis signals and M>N, N is the dimension of the signal to be represented; Perform signal sparse coding, for the signal to be represented y∈R extracted from the multi-view image N , which is expressed as the characteristic basis signal d i The linear combination y=D*a, and the sparse representation coefficient a is solved by the sparse coding algorithm, and the solution model satisfies: Among them, ||α||0 is the L0 pseudo-norm, which is used to constrain the sparsity of coefficient a, D is the feature dictionary, and y represents the signal to be represented; Perform three-dimensional image reconstruction based on the sparse representation coefficient a obtained by linear combination of characteristic basis signals d i Restore the three-dimensional features of multi-view images and ultimately generate high-precision three-dimensional images of the patient's screening area.

8. A mobile C-arm image data acquisition system based on a dual-ring structure for executing the mobile C-arm image data acquisition method based on a dual-ring structure according to any one of claims 1 to 7, characterized in that: include: A dual-ring structure building module is used to build a dual-ring mobile C-arm structure. The dual-ring mobile C-arm structure includes a compensation C-ring, a sliding arm, and a load C-ring. The two C-rings move synchronously to enable the imaging chain to reciprocate around the patient at a large angle. A synchronous motion control module is used to perform synchronous motion control, and realizes synchronous and unidirectional motion of the slide arm along the compensation C-ring and the load C-ring along the slide arm through a ring motion power system via belt drive and gear drive, so that the imaging chain reciprocates around the patient; The multi-mode exposure acquisition module is used to acquire multi-mode exposure during data acquisition. The C-ring angle can be adjusted through human-computer interaction to perform perspective or photographic mode exposure at a fixed angle, or to perform 3D mode exposure at a set frame rate during motion to acquire multi-view image data. The image calibration and 3D reconstruction module is used to perform image calibration and 3D reconstruction. It uses an optical rangefinder to calibrate the image magnification error and performs 3D reconstruction based on multi-view image data through a sparse representation algorithm.

9. A computer device comprising a memory and one or more processors, wherein the memory stores computer code, and when the computer code is executed by the one or more processors, the one or more processors are caused to perform the method according to any one of claims 1 to 7. 10 . A computer-readable storage medium storing computer code, wherein when the computer code is executed, the method according to claim 1 is performed.

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