Root canal fiber pile removing system and method based on digital guide plate guiding

Abstract

The invention discloses a digitized guide plate guidance-based root canal fiber pile removal system and method, and relates to the technical field of oral medical instruments and oral medical treatment, and the system comprises an abnormal structure detection module, a digitized guide plate adjustment module, a removal instrument part, a feedback control system and a fault diagnosis sub-module; according to the invention, the effect of solving the problem of fiber post removal caused by abnormal hyperplasia of jaw callus in special cases is obvious; during image acquisition and preprocessing, the deep learning algorithm enables the abnormal region recognition speed to be improved by about 45%; the abnormal structure detection obtains key data through a low-frequency mechanical wave module; digitized guide plate adjustment can accurately avoid obstacles and guarantee path safety. Deflection, jamming and damage are reduced through instrument dismounting operation; the fault occurrence rate of a feedback control system is reduced by about 60%; the coating is friction-reducing and environment-friendly; the auxiliary positioning device can be quickly calibrated when meeting a deviated rail; all links are coordinated, so that the problems of deflection, jamming and faults of a conventional operation are effectively avoided, and the success rate, safety and stability of the operation are improved.

Description

Technical Field

[0001] The present invention relates to the field of oral medical instruments and oral medical technology, and in particular to a root canal fiber post removal system and method based on digital guide plate guidance. Background Art

[0002] In the existing oral treatment technology, the root canal fiber post removal system and method based on digital guide plate guidance is designed to solve the problems existing in the traditional root canal fiber post removal process. The traditional removal method lacks accuracy and is easy to cause damage to the tooth root and surrounding tissues. With the help of digital technology, this system first obtains accurate three-dimensional data of the patient's mouth through oral scanning, and designs and produces a special digital guide plate based on this. When removing the root canal fiber post, this guide plate is used to provide doctors with accurate path guidance. Doctors can accurately control the direction and depth of the removal tool according to the guidance of the guide plate, so as to remove the fiber post more safely and efficiently, reduce the risk of damage to the tooth root and surrounding tissues, and improve the success rate and quality of root canal fiber post removal surgery, laying a good foundation for subsequent oral restoration treatment.

[0003] In some special cases, such as when the patient has experienced maxillofacial trauma, there are tiny, undetected areas of abnormal callus proliferation inside the jawbone that form after the fracture line heals. The density and hardness of these hyperplastic areas are different from those of normal bone tissue, which may interfere with the imaging quality of the CBCT (cone beam CT) images that the digital guide relies on, making it impossible to accurately identify these abnormal structures during the image acquisition and processing stages. When performing fiber post removal surgery, according to conventional digital guide positioning, the removal instruments may unexpectedly deflect or jam when encountering these abnormal callus areas. This problem caused by potential undetected old maxillofacial trauma is difficult to predict during preoperative planning and routine operations, and cannot be directly solved by simple existing technical means (such as conventional X-ray examinations or CBCT analysis based on normal anatomical structures).

[0004] In view of this, a root canal fiber post removal system and method based on digital guide guidance are provided to overcome the above problems. Summary of the invention

[0005] The object of the present invention is to provide a root canal fiber post removal system and method based on digital guide plate guidance to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides a root canal fiber post removal system based on digital guide plate guidance, comprising:

[0007] Abnormal structure detection module: connected to the pre-detection module that obtains preliminary image information of the jaw region, used to analyze the image to identify the abnormal callus proliferation area after the suspected fracture line heals, and includes a low-frequency mechanical wave detection submodule, which emits 10-50Hz low-frequency mechanical waves to the jaw, and detects the boundary, hardness and density distribution of the abnormal callus proliferation area based on the characteristics of the reflected wave;

[0008] Digital guide adjustment module: Based on the information from the abnormal structure detection module, the bionic optimization algorithm is used to adjust the digital guide positioning data, simulate the decision-making process of the biological nervous system, and quickly calculate the best solution to avoid abnormal areas and guide the removal instrument to accurately approach the root canal fiber post;

[0009] Removal of instrument components: In conjunction with the digital guide plate, the front end is equipped with an adaptive actuator, which contains multiple front-end distributed micro pressure and angle sensors, which can sense the contact between the instrument and the surrounding tissue; when encountering resistance in the abnormal callus area, the intelligent control unit automatically fine-tunes the front end angle and torque of the instrument based on the preset mechanics and machine learning algorithms;

[0010] Feedback control system: connects the removal instrument and the digital guide adjustment module, monitors and feeds back the status and position information of the removal instrument in real time, and also includes a fault diagnosis submodule, which diagnoses the cause and issues an alarm when an abnormality occurs, and provides fault information to the digital guide adjustment module;

[0011] Surface coating of removal instrument: The surface of the removal instrument is preset with organic-inorganic hybrid nano coating.

[0012] Furthermore, the low-frequency mechanical wave detection submodule automatically optimizes the frequency and intensity of the transmitted wave according to the characteristics of the initial detected abnormal area.

[0013] Furthermore, the digital guide plate adjustment module introduces dynamic weight allocation in the process of simulating the biological nervous system by the bionic algorithm, and dynamically allocates weights to the factors affecting the guide plate adjustment according to the real-time information of the feedback control system.

[0014] Furthermore, the intelligent control unit of the adaptive actuator has self-learning capabilities, which are used to optimize the preset mechanical model and machine learning algorithm based on sensor feedback data and abnormal conditions for each demolition operation.

[0015] Furthermore, the fault diagnosis submodule of the feedback control system establishes a fault prediction model when deeply analyzing and mining historical fault data.

[0016] Furthermore, the organic-inorganic hybrid material of the removal device surface coating contains antibacterial nanoparticles.

[0017] Furthermore, the preliminary image information obtained by the pre-detection module is preliminarily screened and classified through an image preprocessing algorithm based on deep learning.

[0018] A method for removing a root canal fiber post based on digital guide guidance comprises the following steps:

[0019] After obtaining preliminary image information of the patient's jaw area through the pre-detection module, the deep learning image pre-processing algorithm is used to screen and classify the images to locate possible abnormal areas;

[0020] The abnormal structure detection module analyzes the preliminary image. If a suspected abnormal callus proliferation area is found, the low-frequency mechanical wave detection submodule is activated to automatically optimize the frequency and intensity of the transmitted wave according to the characteristics of the abnormal area for detailed detection.

[0021] According to the detection results, the digital guide plate adjustment module uses a bionic optimization algorithm with a dynamic weight distribution mechanism to adjust the digital guide plate positioning data;

[0022] The adjusted digital guide is placed in the oral cavity to guide the removal instrument to approach the root canal fiber post. During the removal process, the adaptive actuator at the front end of the removal instrument can adjust the angle and torque in real time according to the sensor feedback based on the self-learning ability of the intelligent control unit to deal with abnormal resistance;

[0023] The feedback control system monitors the status of the removal equipment in real time, and its fault diagnosis submodule uses big data analysis and fault prediction models to diagnose and prevent possible faults in advance;

[0024] After the removal is completed, clean and inspect the surgical area to confirm that the root canal fiber post has been removed and the surrounding tissues are not damaged. The multifunctional coating on the surface of the removal instrument ensures smooth operation and reduces postoperative risks;

[0025] If the demolition equipment deviates from the planned path due to abnormal circumstances during the demolition process, an auxiliary positioning device is used for rapid calibration. The device uses optical tracking technology to monitor the position of the demolition equipment in real time, and communicates with the digital guide adjustment module to make precise position corrections to the demolition equipment.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] By adopting an image preprocessing algorithm based on deep learning, the initial identification speed of abnormal areas is increased by about 45% compared with the traditional image analysis method based on grayscale threshold and morphological analysis. It greatly improves the speed of discovering abnormal areas and the working efficiency of the entire system, effectively avoids abnormal situations that may be missed due to the limitations of traditional image analysis methods, and provides important clues for subsequent precise detection.

[0028] The low-frequency mechanical wave detection submodule emits 10-50Hz low-frequency mechanical waves to the jawbone, and automatically optimizes the frequency and intensity of the transmitted waves based on the characteristics of the abnormal area initially detected. It can accurately detect the boundary, hardness and density distribution information of the abnormal callus proliferation area. These key data cannot be obtained by traditional methods relying on conventional imaging observations and doctors' experience and judgment. It provides a reliable data basis for subsequent surgical operations and effectively solves the problem of increased surgical risks caused by the difficulty in identifying abnormal structures.

[0029] The digital guide adjustment module uses an optimization algorithm based on bionics and with a dynamic weight allocation mechanism to adjust the digital guide positioning data, simulating the adaptive learning and decision-making process of the biological nervous system. According to the real-time information provided by the feedback control system, the weights of factors such as the position of the abnormal area and the status of the removal instrument in the guide adjustment plan are dynamically allocated. In actual surgery, it successfully avoids the area of ​​abnormal callus proliferation, provides a safe and accurate path for the removal instrument to approach the root canal fiber post, and keeps the closest distance between the removal instrument and the callus area above 3mm, avoiding the deflection or jamming caused by the collision between the removal instrument and the abnormal callus area that may occur according to conventional digital guide positioning, thereby ensuring the accuracy and safety of the removal path.

[0030] The adaptive actuator at the front end of the removal instrument component relies on the self-learning ability of its intelligent control unit to adjust the angle and torque in real time according to sensor feedback to cope with abnormal resistance, minimizing damage to the tooth and surrounding tissues, demonstrating a unique ability to respond to special abnormal situations in a refined and intelligent manner, and significantly reducing surgical risks.

[0031] The fault diagnosis submodule of the feedback control system uses big data analysis and fault prediction models to diagnose and prevent possible faults in advance. Through real-time analysis of the working data and position information of the demolition instrument, once abnormal fluctuations or deviations from the normal range of the working parameters are found, the cause of the fault is quickly diagnosed and an alarm is sounded. At the same time, fault information is provided to the digital guide adjustment module, effectively avoiding possible faults, providing a strong guarantee for the stable operation of the demolition system, and solving the risk of surgical interruption or failure due to sudden faults during the operation.

[0032] The multifunctional coating on the surface of the removal instrument is made of a new type of organic-inorganic hybrid material, which has self-lubricating and wear-resistant properties. When the removal instrument contacts the callus area, the coating reduces the friction coefficient between the instrument and the callus by about 35%, which can effectively reduce the friction between the instrument and the callus, avoiding damage to the instrument due to jamming, and also reducing the risk of damage to surrounding tissues. Moreover, the coating can automatically decompose into harmless small molecules after surgery for easy removal from the oral cavity, avoiding potential hazards and further ensuring the safety of the operation and postoperative recovery effect.

[0033] The auxiliary positioning device uses optical tracking technology. When the demolition instrument deviates from the predetermined path, it can monitor the position of the demolition instrument in real time, and communicate with the digital guide adjustment module to accurately correct the position of the demolition instrument, quickly returning to the correct demolition path within 8 seconds. It provides an effective supplementary means for the demolition method to deal with complex situations, significantly improves the success rate and stability of demolition surgery in the face of various complex situations, and solves the problem of surgical stagnation or failure due to unexpected situations.

[0034] The present invention effectively solves from multiple aspects the many problems caused by fiber post removal surgery in special cases due to undiscovered abnormal callus proliferation areas inside the jaw due to maxillofacial trauma, significantly improves the success rate, safety and stability of the surgery, and provides an efficient and reliable solution for the treatment of similar complex cases in the field of oral surgery, which has important clinical application value and broad market prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 The present invention is a schematic diagram of a root canal fiber post removal system and method based on digital guide plate guidance. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] See also Figure 1 , the present invention provides a technical solution:

[0038] See also Figure 1 As shown, an embodiment of a root canal fiber post removal system and method based on digital guide guidance:

[0039] Example:

[0040] Scenario description:

[0041] A 45-year-old male patient suffered severe maxillofacial trauma 5 years ago. He recovered well after treatment, but recently needed root canal fiber post removal surgery due to oral problems. Preoperative CBCT image acquisition revealed some suspected abnormal images in the jaw area, but due to the abnormal callus proliferation area formed after the healing of the tiny fracture lines left by the previous maxillofacial trauma, its density was about 35% higher than that of normal bone tissue, and its hardness was increased by about 45% (obtained by nanoindentation hardness testing and X-ray density measurement of local bone tissue samples in this area). This significant difference made it difficult to accurately identify and locate these abnormal structures in conventional CBCT image analysis, which brought great challenges to the surgery.

[0042] Dismantling system and method steps:

[0043] Image acquisition and preprocessing:

[0044] First, the pre-detection module obtains preliminary image information of the patient's jaw area, including X-ray images and CBCT images.

[0045] Then, these images were preliminarily screened and classified using a deep learning-based image preprocessing algorithm. In the image analysis of this patient, compared with the traditional image analysis method based on grayscale threshold and morphological analysis, this algorithm increased the initial recognition speed of abnormal areas by about 45%, and was able to quickly identify areas where abnormal structures may exist, greatly improving the speed of discovering abnormal areas and the work efficiency of the entire system. For example, in this case, the traditional method took about 15 minutes to perform a preliminary analysis of the image, but through the deep learning algorithm, 4 suspected abnormal areas were quickly marked in just 8 minutes, providing important clues for subsequent precise detection and effectively avoiding abnormalities that may be missed due to the limitations of traditional image analysis methods.

[0046] Abnormal structure detection:

[0047] The abnormal structure detection module analyzes the preliminary image information and quickly identifies areas suspected of abnormal callus proliferation, and then activates the low-frequency mechanical wave detection submodule.

[0048] The low-frequency mechanical wave detection submodule emits 10-50Hz low-frequency mechanical waves to the jawbone, and automatically optimizes the frequency and intensity of the emitted waves based on the characteristics of the abnormal area initially detected. In this operation, this unique detection method accurately detected the boundary, hardness and density distribution information of the abnormal callus proliferation area. These key data cannot be obtained by traditional methods that rely on conventional imaging observations and doctors' experience. For example, the detected abnormal callus proliferation area is located near the root canal fiber post. Its hardness is significantly higher than the surrounding normal bone tissue, and the boundary is irregular in shape with an area of ​​about 0.6cm 2(Derived through modeling and analysis of low-frequency mechanical wave reflection data.) This precise detection result provides a reliable data basis for subsequent surgical operations, allowing doctors to understand the complex conditions of the surgical area in advance, effectively solving the problem of increased surgical risks caused by the difficulty in identifying abnormal structures.

[0049] Digital guide adjustment:

[0050] According to the detection results of the low-frequency mechanical wave detection submodule, the digital guide plate adjustment module uses an optimization algorithm based on bionics and with a dynamic weight distribution mechanism to adjust the digital guide plate positioning data.

[0051] This algorithm simulates the adaptive learning and decision-making process of the biological nervous system, and dynamically allocates the weights of factors such as the position of the abnormal area and the state of the removal instrument in the guide adjustment plan based on the real-time information provided by the feedback control system. In this operation, this intelligent, dynamically fine-tuned guide adjustment method successfully avoided the abnormal callus proliferation area, providing a safe and accurate path for the removal instrument to approach the root canal fiber post. For example, the positioning data of the guide was precisely adjusted according to the position and shape of the abnormal area, so that the closest distance between the removal instrument and the callus area was always maintained at more than 3mm (obtained through real-time optical tracking measurement during the operation), avoiding the deflection or jamming caused by the collision between the removal instrument and the abnormal callus area that may occur according to conventional digital guide positioning, and ensuring the accuracy and safety of the removal path.

[0052] Removal of equipment operation:

[0053] Place the adjusted digital guide into the oral cavity to guide the removal of instrument components close to the root canal fiber post.

[0054] During the removal process, the adaptive actuator at the front end of the removal instrument component adjusts the angle and torque in real time to deal with abnormal resistance based on the self-learning ability of its intelligent control unit and sensor feedback. When the removal instrument encounters resistance caused by the abnormal callus area, multiple micro pressure sensors and angle sensors can quickly sense the contact pressure and relative angle changes between the instrument and the surrounding tissue, and transmit this information to the intelligent control unit. The intelligent control unit automatically fine-tunes the angle of the front end of the instrument and applies torque based on the preset mechanical model and machine learning algorithm to maintain stable advancement and minimize damage to the tooth and surrounding tissue. For example, in this operation, when the removal instrument approached the area of ​​abnormal callus proliferation, the intelligent control unit promptly adjusted the angle of the front end of the instrument based on the data fed back by the sensor, allowing it to smoothly bypass the callus area and continue to advance the removal work, avoiding instrument deflection and jamming due to abnormal resistance. Compared with the general structural improvement design of conventional demolition instruments, in this operation, the average deflection angle of the demolition instrument caused by abnormal resistance was controlled within 3° (obtained from the measurement data of the built-in gyroscope of the instrument), and the number of jams was reduced by about 75% (compared with historical data of similar operations performed with conventional instruments), which significantly reduced the surgical risk and demonstrated a unique ability to respond to special abnormal situations in a refined and intelligent manner.

[0055] Feedback control and fault diagnosis:

[0056] The feedback control system monitors the status of the demolition equipment in real time, and its fault diagnosis submodule uses big data analysis and fault prediction models to diagnose and prevent possible faults in advance.

[0057] In this operation, the fault diagnosis submodule analyzes the working data and position information of the removal instrument in real time. Once the working parameters are found to fluctuate abnormally or deviate from the normal range, the fault cause is quickly diagnosed and an alarm is issued, and the fault information is provided to the digital guide adjustment module to ensure the smooth progress of the operation. For example, during the removal process, when the torque of the removal instrument suddenly increases by more than 25% of the normal range (determined based on the big data statistical analysis of the normal working torque range of this type of instrument), the fault diagnosis submodule immediately detects this abnormal situation and judges through big data analysis that it may be caused by the increased friction between the instrument and the callus area. Therefore, an alarm is issued in time and information is sent to the digital guide adjustment module to adjust the guide position, and the operator is prompted to adjust the operation mode of the removal instrument, which effectively avoids possible faults and improves the reliability and success rate of the operation. This fault diagnosis and prediction function based on big data is rare in related patents, which provides a strong guarantee for the stable operation of the removal system and solves the risk of interruption or failure of the operation due to sudden faults during the operation. Through the application of this fault diagnosis submodule, the failure rate during the operation is reduced by about 60% (based on the comparison of the failure statistics of similar operations in the past of this team).

[0058] Removal of surface coating of instruments:

[0059] During the whole removal process, the multifunctional coating on the surface of the removal instrument plays an important role. The coating is made of a new organic-inorganic hybrid material and has self-lubricating and anti-wear properties.

[0060] When encountering an area of ​​abnormal callus proliferation, the coating can reduce friction and jamming, thereby improving the durability and service life of the instrument. For example, in this operation, when the removal instrument came into contact with the callus area, the coating reduced the friction coefficient between the instrument and the callus by about 35% (derived from friction tests of coated and untreated instruments in contact with callus samples in a simulated surgical environment), effectively reducing the friction between the instrument and the callus, allowing the instrument to operate more smoothly, avoiding damage to the instrument due to jamming, and also reducing the risk of damage to surrounding tissues. Moreover, the coating can automatically decompose into harmless small molecules after surgery to facilitate removal from the mouth, avoiding potential hazards. Different from the existing patents that only focus on the basic functions of conventional lubrication and corrosion protection, it has the unique characteristics of multi-function and environmental friendliness, further ensuring the safety of surgery and postoperative recovery.

[0061] Auxiliary positioning (to deal with complex situations):

[0062] During the removal process, due to the complexity of the callus area, the removal instrument once deviated from the predetermined path. At this time, the auxiliary positioning device was used for rapid calibration.

[0063] The device uses optical tracking technology to monitor the position of the removal instrument in real time, and communicates with the digital guide adjustment module to make precise position corrections to the removal instrument. For example, when the removal instrument deviates from the path, the optical tracking system immediately captures this situation and transmits the position information to the digital guide adjustment module. The module recalculates and adjusts the guide direction of the guide based on this information, and sends instructions to the intelligent control unit of the removal instrument to automatically adjust the angle and position, and quickly return to the correct removal path within 8 seconds (derived by the time recording of the optical tracking data), ensuring that the removal operation can continue smoothly. This auxiliary positioning step provides an effective supplementary means for the removal method to deal with complex situations, significantly improves the success rate and stability of the removal operation in the face of various complex situations, and solves the problem of surgical stagnation or failure due to unexpected situations.

[0064] Summarize:

[0065] By using the root canal fiber post removal system and method based on digital guide guidance, many problems caused by the fiber post removal surgery in special cases due to the presence of undiscovered abnormal callus proliferation areas inside the jaw due to maxillofacial trauma have been successfully solved. From efficient abnormal area recognition in the image acquisition and preprocessing stage, to accurate data acquisition in the abnormal structure detection stage, to the intelligent adjustment of the digital guide, the refined operation of the removal instrument, the reliable guarantee of the feedback control system, and the multifunctional protection of the surface coating of the removal instrument and the emergency treatment of the auxiliary positioning device, each link is closely coordinated and works together, effectively avoiding the problems of removal instrument deflection and jamming, surgical failure, and damage to surrounding tissues that may occur according to conventional methods. Through specific data comparison, such as the improvement of abnormal area recognition speed, the control of the deflection angle of the removal instrument, the reduction of jamming times, the reduction of the occurrence rate of failures, and the reduction of the friction coefficient, the success rate, safety and stability of the operation are significantly improved, providing an efficient and reliable solution for the treatment of similar complex cases in the field of oral surgery, with important clinical application value and broad market prospects.

Claims

1. A root canal fiber post removal system based on digital guide plate guidance, characterized in that: include: Abnormal structure detection module: connected to the pre-detection module that obtains preliminary image information of the jaw region, used to analyze the image to identify the abnormal callus proliferation area after the suspected fracture line heals, and includes a low-frequency mechanical wave detection submodule, which emits 10-50Hz low-frequency mechanical waves to the jaw, and detects the boundary, hardness and density distribution of the abnormal callus proliferation area based on the characteristics of the reflected wave; Digital guide adjustment module: Based on the information from the abnormal structure detection module, the bionic optimization algorithm is used to adjust the digital guide positioning data, simulate the decision-making process of the biological nervous system, and quickly calculate the best solution to avoid abnormal areas and guide the removal instrument to accurately approach the root canal fiber post; Removal of instrument components: In conjunction with the digital guide plate, the front end is equipped with an adaptive actuator, which contains multiple front-end distributed micro pressure and angle sensors, which can sense the contact between the instrument and the surrounding tissue; when encountering resistance in the abnormal callus area, the intelligent control unit automatically fine-tunes the front end angle and torque of the instrument based on the preset mechanics and machine learning algorithms; Feedback control system: connects the removal instrument and the digital guide adjustment module, monitors and feeds back the status and position information of the removal instrument in real time, and also includes a fault diagnosis submodule, which diagnoses the cause and issues an alarm in case of abnormality, and provides fault information to the digital guide adjustment module; an organic-inorganic hybrid nano coating is preset on the surface of the removal instrument.

2. A root canal fiber post removal system based on digital guide plate guidance as claimed in claim 1, characterized in that: The low-frequency mechanical wave detection submodule automatically optimizes the frequency and intensity of the transmitted wave according to the characteristics of the initial detected abnormal area.

3. The root canal fiber post removal system based on digital guide plate guidance according to claim 1, characterized in that: The digital guide adjustment module introduces dynamic weight allocation in the process of bionic algorithm simulating the biological nervous system, and dynamically allocates weights to factors affecting the guide adjustment according to the real-time information of the feedback control system.

4. The root canal fiber post removal system based on digital guide plate guidance according to claim 1, characterized in that: The intelligent control unit of the adaptive actuator has self-learning capabilities and is used to optimize the preset mechanical model and machine learning algorithm based on sensor feedback data and abnormal conditions for each removal operation.

5. The root canal fiber post removal system based on digital guide plate guidance according to claim 1, characterized in that: The fault diagnosis submodule of the feedback control system establishes a fault prediction model when deeply analyzing and mining historical fault data.

6. The root canal fiber post removal system based on digital guide plate guidance according to claim 1, characterized in that: Organic-inorganic hybrid materials containing antimicrobial nanoparticles for removal of device surface coatings.

7. The root canal fiber post removal system based on digital guide plate guidance according to claim 1, characterized in that: The preliminary image information obtained by the pre-detection module is preliminarily screened and classified through an image preprocessing algorithm based on deep learning.

8. A method for removing root canal fiber posts based on digital guide plate guidance, characterized in that: The following steps are involved: After obtaining preliminary image information of the patient's jaw area through the pre-detection module, the deep learning image pre-processing algorithm is used to screen and classify the images to locate possible abnormal areas; The abnormal structure detection module analyzes the preliminary image. If a suspected abnormal callus proliferation area is found, the low-frequency mechanical wave detection submodule is activated to automatically optimize the frequency and intensity of the transmitted wave according to the characteristics of the abnormal area for detailed detection. According to the detection results, the digital guide plate adjustment module uses a bionic optimization algorithm with a dynamic weight distribution mechanism to adjust the digital guide plate positioning data; The adjusted digital guide is placed in the oral cavity to guide the removal instrument to approach the root canal fiber post. During the removal process, the adaptive actuator at the front end of the removal instrument can adjust the angle and torque in real time according to the sensor feedback based on the self-learning ability of the intelligent control unit to deal with abnormal resistance; The feedback control system monitors the status of the removal equipment in real time, and its fault diagnosis submodule uses big data analysis and fault prediction models to diagnose and prevent possible faults in advance; After the removal is completed, clean and inspect the surgical area to confirm that the root canal fiber post has been removed and the surrounding tissues are not damaged. The multifunctional coating on the surface of the removal instrument ensures smooth operation and reduces postoperative risks; If the demolition equipment deviates from the planned path due to abnormal circumstances during the demolition process, an auxiliary positioning device is used for rapid calibration. The device uses optical tracking technology to monitor the position of the demolition equipment in real time, and communicates with the digital guide adjustment module to make precise position corrections to the demolition equipment.

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