6025 results about "Oral cavity" patented technology

The present invention relates to the technical field of stomatology. Provided is an auxiliary dental implant generation method based on a diffusion model. The method in the present invention comprises: acquiring oral CBCT image data of historical patients, preprocessing the oral CBCT image data of the historical patients to obtain a CBCT image dataset, using the CBCT image dataset to train a multi-task segmentation network, and using the segmentation network to obtain an intraoral tissue segmentation result; using the intraoral tissue segmentation result to train detection networks from the three dimensions of a cross-sectional plane, a coronal plane and a sagittal plane, respectively; using the detection networks to obtain detection results in the three directions of the cross-sectional plane, the coronal plane and the sagittal plane; fusing the detection results in the three directions of the cross-sectional plane, the coronal plane and the sagittal plane, and using a majority voting algorithm to construct a three-dimensional bounding box, so as to acquire an edentulous area; and using the intraoral segmentation result and the edentulous area as prompt information to guide, by means of an iterative process, a network to generate a post-implantation effect. The implantation effect obtained by the present invention is highly accurate, thereby providing a more precise auxiliary tool for stomatology.

The invention discloses a three-dimensional stomatognathic model reconstruction system based on multi-modal data fusion. The system comprises a multi-modal data input unit, a template deformation reconstruction unit, a registration fusion unit, a multi-source data integration unit and an output unit. Through fusion processing of a CBCT image, an oral cavity vision measurement model and facial scanning data, a body deformation algorithm is adopted to couple biomechanical characteristics to realize craniojaw template deformation, and a non-rigid ICP algorithm is combined for dynamic regulation and control to realize facial template adaptation. A deep neural network is innovatively constructed to segment CBCT gingival data, the CBCT gingival data is fused with an oral cavity vision measurement model, and high-precision tooth reconstruction is realized by applying a differential geometry multi-scale curvature field segmentation and adversarial edge optimization technology. Through a composite registration strategy combining adaptive rigid registration and non-rigid registration, an occlusal plane constraint mechanism and an orbital curvature extreme point matching algorithm are innovatively introduced, finally, multi-source data high-precision registration fusion is realized, and a three-dimensional oral-jaw system model with anatomical structure integrity and clinical precision can be generated.

The invention relates to the technical field of medical diagnosis, in particular to a dysphagia detection and automatic scoring system based on a high-resolution acoustic sensor. Comprising a three-dimensional curved surface type acoustic sensing array module, a self-adaptive environment noise compensation module, a swallowing stage dynamic segmentation module, a multi-dimensional feature extraction engine, a swallowing abnormal mode classifier and a dynamic weight scoring model. A self-adaptive environment noise compensation module, a time-frequency domain feature extraction module and a dynamic weight scoring model are combined, the swallowing process is monitored and scored in real time, the system automatically identifies and analyzes acoustic features of an oral cavity preparation period, a pharyngeal period and an esophageal period, and through multi-dimensional feature fusion, dynamic weighting and neural network optimization, the swallowing process is monitored and scored in real time. The method has the advantages of being non-invasive, easy and convenient to operate, high in real-time performance and the like, and can be widely applied to early screening, evaluation and follow-up visit of clinical dysphagia.

The invention discloses an oral tooth lesion AI auxiliary diagnosis system, which belongs to the field of artificial intelligence and comprises an image acquisition module, a three-dimensional modeling module, a lesion marking module, a dual-channel feature extraction module, a cross-modal diagnosis reasoning module, a lesion evolution trend prediction module and a dynamic risk level generation module. The image acquisition module utilizes multi-frequency structured light and a polarization camera to cooperatively acquire oral images; the three-dimensional modeling module is used for reconstructing an upper and lower jaw three-dimensional structure based on edge constraint splicing point clouds and registering images to form double-view fusion data; the lesion labeling module fuses expert labeling and weak supervision pseudo labels to generate joint labels; the dual-channel module extracts skeleton and texture features; the reasoning module realizes cross-modal semantic coupling through an image-text co-occurrence graph; the evolution prediction module models a lesion change path based on the time reversal causal network; and the risk module outputs a five-level risk and re-injects the embedded vector to strengthen prediction. The beneficial effects are that diagnosis intelligence and clinical decision support level are obviously improved.

The invention discloses an oral cavity panoramic image processing system, and the system comprises an image collection module which is used for collecting an initial oral cavity panoramic image containing a plurality of oral cavity diseases; the image processing module is connected with the image acquisition module and is used for performing target detection and instance segmentation labeling on the initial oral panoramic image and expanding a training data set by adopting a data enhancement technology to obtain a target oral panoramic image; a model construction module connected with the image processing module and used for training an MMC-YOLO network model through the target oral panoramic image to obtain a target MMC-YOLO network model; and the analysis and detection module is connected with the model construction module, and is used for performing synchronous detection of tooth concurrent oral diseases, comprehensive analysis of multi-dimensional pathological information and accurate recognition of multi-scale pathological changes through the target MMC-YOLO network model to obtain an analysis result. The system provided by the invention realizes synchronous detection and accurate grading of multiple types of focuses in the oral panoramic image.

The invention provides an oral health monitoring method and system based on three-dimensional reconstruction and multi-feature constraint, and relates to the technical field of medical data processing and oral monitoring, and the method comprises the steps: obtaining a multi-angle high-definition image and depth data in an oral cavity; performing semantic segmentation on the preprocessed multi-angle high-definition image, and identifying a tooth structure and a key region in an oral cavity; constructing a three-dimensional oral cavity model by using an edge-guided depth reconstruction method; a timestamp is introduced, the depth data, the tooth structure in the oral cavity and the key area are mapped to a three-dimensional oral cavity model, on the basis of the three-dimensional space dimension, the time dimension and the key point distribution dimension are added, and a multi-dimensional dynamic oral cavity model is constructed; based on the multi-dimensional dynamic oral cavity model, analyzing the evolution trend of the key region through a space-time dynamic prediction network, predicting future evolution risks, and obtaining a risk assessment result; and generating a health management suggestion according to a risk assessment result, and feeding back the health management suggestion to the multi-dimensional dynamic oral cavity model to form a closed-loop feedback mechanism.

A water flosser includes a shell, a pumping assembly and an oral rinse capsule. A water storage chamber and a liquid outlet communicated to the water storage chamber are provided inside the shell, and the liquid outlet is located at a bottom of the water storage chamber. The pumping assembly is arranged in the shell. A pumping port of the pumping assembly extends to a position, close to the liquid outlet, at the bottom of the water storage chamber. The pumping assembly is configured to pump liquid and spray the liquid out along a nozzle. An oral rinse accommodating chamber is provided in the oral rinse capsule. The oral rinse capsule is arranged at a bottom of the shell. The oral rinse accommodating chamber is communicated to the liquid outlet.

A water flosser includes a shell and an oral rinse capsule. A capsule accommodating chamber is arranged at a bottom of the shell. A clamping assembly is arranged in the shell. A clamping end of the clamping assembly is threaded out of an inner wall of the capsule accommodating chamber of the shell. The oral rinse capsule is detachably inserted into the capsule accommodating chamber. A clamping slot is provided on a surface of the oral rinse capsule. The clamping end of the clamping assembly is detachably clamped into the clamping slot. By the arrangement of the above structure, the oral rinse capsule is inserted into the capsule accommodating chamber, and the clamping end of the clamping assembly is clamped into the clamping slot, which can effectively fix the oral rinse capsule and make the structure of the product more stable.

The invention relates to the technical field of denture manufacturing, and discloses a high-precision digital complete denture 3D printing method which comprises the following steps: obtaining an initial denture model of a target object; acquiring occlusal point adjustment data; acquiring actual adjustment data; adjusting the initial false tooth model based on the actual adjustment data, and converting the adjusted initial false tooth model into a 3D printing instruction for 3D printing; according to the method, stress distribution during occlusion is simulated through finite element analysis, a three-dimensional occlusion thermodynamic diagram is obtained and input into a constructed CNN network model, occlusion point adjustment data are obtained, adjustment data of effective occlusion contact points are mapped into a solid model, and actual adjustment data are obtained; three-dimensional data of the oral cavity of a patient is obtained through a scanner, digital analysis is conducted in combination with a neural network model, the denture manufacturing precision is improved, manufacturing is conducted in a 3D printing mode, the manufacturing efficiency is high, the patient feels comfortable when wearing the denture and occludes the denture well, and the problem of diet difficulty of the implant patient is solved in time.

The invention relates to the field of oral medical diagnosis, and discloses an intraoral image-based AI enhanced real-time occlusion detection system, which comprises a multi-source intraoral image acquisition module for acquiring dynamic oral image data through a high-definition oral endoscope and recording a three-dimensional structure of a tooth surface by combining a laser scanning device, meanwhile, force distribution of an occlusion contact point is collected through a pressure sensor array; the multi-source intraoral image acquisition module comprises a timestamp synchronization unit and is used for performing multi-source synchronization on an oral image frame sequence and occlusal force distribution data by utilizing a unified timestamp; through the multi-source in-port image acquisition module, synchronous acquisition of dynamic images, three-dimensional structure data and bite force distribution is realized, and time sequence consistency of the data is ensured through timestamp marking. Compared with a traditional single data source collection mode, the multi-source collection can comprehensively record dynamic characteristics in the occlusion process, rich and accurate input is provided for subsequent AI analysis, and data missing or collection deviation is avoided.

The invention discloses a data processing method and system for a dental three-dimensional model, and relates to the technical field of dental three-dimensional modeling, and the method comprises the steps: obtaining initial data of oral cavity scanning, recognizing a tooth type in the initial data, and determining a corresponding tooth surface reflection parameter according to the tooth type; generating scanning parameter combinations for different tooth positions according to the tooth surface reflection parameters and the tooth anatomical structure; tooth point cloud data are collected, and a tooth enamel reflective area and a shadow shielding area are identified; performing light reflection removal processing on the enamel light reflection area, performing data completion on the shadow shielding area, and generating corrected tooth point cloud data; and performing registration fusion on the corrected tooth point cloud data to generate a dental three-dimensional model containing a complete dentition. According to the method, the problem of data missing caused by enamel light reflection and adjacent tooth shielding is solved through a differential scanning strategy and regional data processing aiming at specific optical characteristics of teeth, and automatic construction of a high-quality dental three-dimensional model is realized.

The invention discloses an automatic identification method, device and equipment for mandibular wisdom teeth, a medium and a product, and relates to the field of image processing.The method comprises the steps that an oral maxillofacial cone beam computed tomography image is obtained; segmenting and positioning the mandibular wisdom tooth region-of-interest in the oral and maxillofacial cone beam computed tomography image by adopting a pre-trained first deep learning model to obtain a mandibular wisdom tooth segmentation mask image, and cutting a mandibular wisdom tooth region-of-interest image from the oral and maxillofacial cone beam computed tomography image; adopting a pre-trained second deep learning model to perform three-dimensional segmentation on the mandibular wisdom tooth region-of-interest image to obtain a three-dimensional segmentation mask image; and according to the mandibular wisdom tooth region-of-interest image and the three-dimensional segmentation mask image, determining a mandibular wisdom tooth recognition result by adopting a pre-trained third deep learning model. The identification accuracy and the identification efficiency of the wisdom teeth of the lower jaw are improved.

The invention discloses a tooth intelligent segmentation and parameterized bionic reconstruction method fusing multi-modal data, and belongs to the field of artificial intelligence and computer-aided biomedical engineering. The method comprises a CBCT intelligent segmentation module, an intraoral scanning intelligent segmentation module, an internal tissue segmentation module, a point cloud generation registration module and a parameterized bionic reconstruction module. The point cloud generation registration module further comprises a point cloud generation sub-module and a point cloud registration sub-module; the parameterized bionic reconstruction module further comprises a dentin reconstruction sub-module, a cancellous bone reconstruction sub-module and a gingival reconstruction sub-module. The invention aims to realize tooth semantic segmentation, point cloud reconstruction and parameterized bionic modeling of an organization structure under cross-modal data fusion, and provides high-precision bionic internal structure information for teeth in combination with an artificial intelligence model and parameterized modeling.

The invention discloses a digital dental implant bridge and false tooth and false tooth automatic adaptation and production system based on CBCT (cone beam computed tomography) and oral scanning data and a control method thereof, which are used for realizing automatic design, adaptation and production of a dental implant bridge and false teeth and false teeth and fusing the CBCT data and the oral scanning data to generate a three-dimensional oral cavity digital model. An automatic modeling technology based on deep learning is used for analyzing the occlusion relation, the adjacent tooth form and the implant angle of a patient, and an implant tooth bridge and false teeth are automatically designed to obtain a three-dimensional model of the prosthesis. A computer vision technology or a three-dimensional scanning technology is adopted to detect the consistency of the size and shape of a produced finished product and the three-dimensional model; and digital try-on is performed through an augmented reality (AR) technology, so that rapid adjustment of various parameters of the product is realized.

The invention discloses a lactobacillus delbrueckii subsp. Lactis TG001 and application thereof in improving oral health, and belongs to the technical field of probiotic application, the preservation number of the lactobacillus delbrueckii subsp. Lactis TG001 is CCTCC NO: M 20241941, the preservation place is China Center for Type Culture Collection in Wuhan, and the preservation date is September 9, 2024. The lactobacillus delbrueckii subsp. Lactis TG001 has a good inhibition effect on common oral pathogens such as streptococcus mutans and porphyromonas gingivalis, particularly can inhibit the growth of cariogenic bacteria streptococcus mutans by generating hydrogen peroxide and remove biofilm formation, and has good tolerance to antibacterial substances in an oral environment. Therefore, the oral cavity diseases such as dental caries, periodontitis and ozostomia can be prevented, the micro-ecological environment of the oral cavity is effectively improved, meanwhile, the peculiar smell of the oral cavity is relieved, and good application prospects are achieved in preparation of products for preventing and / or treating the oral cavity diseases such as dental caries and periodontitis.

The invention relates to the technical field of digital data processing, in particular to a finite element analysis method and system for a full-mouth edentulous movable denture, and the method comprises the steps: obtaining a CT image of the oral cavity of a patient, constructing a three-dimensional finite element model through a finite element analysis method, and carrying out the grid division of the three-dimensional finite element model, obtaining a unit size and a maximum deviation coefficient of each grid, and a pressure trend vector of each grid in each dynamic occlusion process; determining the shape complex weight of each grid; determining a pressure difference degree, a stress sensitivity degree, a stress dispersion degree and a structure disorder characteristic value of each grid; obtaining each defect grid; calculating the number of expanded neighborhood layers of each defect grid; and refining the grids, and optimizing the false tooth according to a simulation result of occlusion simulation of the three-dimensional finite element model. According to the method, local stress changes can be accurately captured, the accuracy of finite element analysis on false tooth stress analysis is improved, and the pain feeling of a patient during occlusion is reduced.

The invention relates to a dissolvable food gel gradient-based swallowing ability dynamic quantification method, which comprises the following steps of: constructing a microstructure unit consisting of an instantaneous surface attachment area and a middle-stage debonding layer in dissolvable food gel, and simulating early-stage sensing delay and middle-stage release response in a swallowing process; different material behavior reactions are generated in the front stage, the middle stage and the rear stage of swallowing by regulating and controlling the hydration diffusion rate, the surface tension and the internal cohesion difference value of the gel, and the gel of each stage corresponds to the set micro-viscosity and release coupling ratio, so that swallowing strategies of different stages are adapted; controllable disintegration temperature-sensing microparticles or traceable microcapsules are partially embedded in the food gel, the food gel is detained in a pharyngeal cavity after being swallowed, and the removal efficiency after swallowing is detected according to migration behaviors within a set time window; after swallowing, the reduction behaviors of the oral cavity, the tongue body and the throat muscle group are monitored, and when the characteristic action of reduction delay, secondary mouth opening, repeated swallowing or pharyngeal itching occurs, it is judged that the swallowing behavior closed loop is interrupted.

The invention relates to the technical field of computers, discloses a tooth three-dimensional precision correction method and system based on multi-source oral data fusion, and aims to solve the problems of low registration precision, serious geometric distortion and lack of function oriented optimization of multi-modal oral data in the prior art. The method comprises the following steps: synchronously obtaining intraoral scanning, CBCT and face three-dimensional point cloud data; carrying out format conversion, denoising and grid simplification preprocessing; tooth surface morphology, root canal anatomy and soft tissue contour features are extracted and coded into uniform feature tensors; and multi-modal data space alignment is realized through staged rigid and non-rigid registration. By means of the scheme, the multi-source data fusion precision and the tooth form restoration accuracy are remarkably improved, full-process automatic efficient processing is achieved, and the clinical real-time performance and high-precision diagnosis and treatment requirements are met.

The invention relates to the technical field of oral health monitoring, and discloses an oral detection method based on an intelligent tooth socket. The method comprises the following steps: acquiring an original oral cavity pressure time sequence and frequency domain characteristics through an intelligent tooth socket, determining an optimized decomposition parameter, and performing multi-scale decomposition on an original signal to generate a multi-scale oral cavity signal component; nonlinear dynamic features are extracted, a component complexity index is obtained, and key signal components related to oral health are screened out; generating a personalized physiological response frequency in combination with the user oral cavity baseline features, the real-time occlusion state and the component complexity index; reconstructing an oral cavity physiological feature sequence based on the key signal component and the personalized physiological response frequency, and separating a low-frequency component and a high-frequency component through modal decomposition; identifying oral cavity abnormity categories according to the two components, establishing a mapping relation with a diagnosis result, and generating an oral cavity health detection instruction. According to the method, convenient and comprehensive oral cavity detection can be realized, the detection adaptability and precision are improved, and support is provided for oral cavity health management.

The invention relates to the technical field of oral X-ray image recognition, in particular to an intelligent oral X-ray film lesion area recognition system based on artificial intelligence. The method comprises the following steps: obtaining gray level change characteristics of each tooth region in an oral X-ray image according to gray level and gradient distribution in each tooth region; obtaining an optimal factor according to the gray change feature similarity between different regions, and further selecting a standard tooth region; obtaining a ray absorption coefficient according to the gray difference of different areas and the difference of the optimal factors; obtaining caries area possibility of the pixel points according to the positions of the pixel points in the tooth area; and the caries area is identified. According to the method, the caries area in the oral X-ray image is accurately segmented, and finally accurate treatment can be carried out on a patient.

The invention discloses a mandibular neural tube automatic segmentation method based on multi-view guidance, and relates to the technical field of oral medical treatment. Comprising the following steps: collecting original oral cavity CBCT image data, and performing preprocessing; sending the preprocessed image data into a mandible segmentation network, and segmenting a mandible region containing a mandible neural tube; a contrast enhancement technology is adopted for the segmented mandible area; projecting the processed mandible image along three orthogonal tangent planes of a coronal plane, a sagittal plane and a cross section; performing key point detection on the mandibular neural tubes on the three projection planes by using the trained key point detection network to obtain shape information of the mandibular neural tubes; and the features are combined with texture direction features to be input into a three-dimensional CBCT mandibular neural tube segmentation network, and accurate 3D segmentation is carried out. Two-dimensional missing space information is avoided, and mandibular neural tube segmentation is more complete and accurate.

The embodiment of the invention discloses a root canal feature form extraction method, device and equipment based on CBCT data and a medium, and belongs to the technical field of stomatology and medical image.The method comprises the steps that filtering denoising and dental pulp segmentation processing are carried out on a CBCT image, and surface drawing three-dimensional reconstruction is carried out on a tooth root canal to generate a three-dimensional model; based on regular point cloud data in the three-dimensional model, adopting a point-surface method to realize curved surface reconstruction, and generating a root canal entity model; and performing coordinate alignment processing on the root canal solid model in a three-dimensional space, and measuring the length of the root canal, the direction of a root canal orifice, the curvature of the root canal and the depth of dental pulp by fitting the approximate center line of the root canal. According to the method, the corresponding three-dimensional model is quickly reconstructed based on the CBCT cross-sectional image obtained by scanning the teeth of the patient, and related data such as the dental pulp depth and the size of the root canal orifice are acquired from the three-dimensional model of the teeth so as to assist the oral surgery.

The invention discloses an MOF-CQD enzyme-sensitive FRET hydrogel diagnosis and treatment probe as well as a preparation method and application thereof, and belongs to the technical field of biomedical detection and treatment. The probe takes a carboxyl carbon quantum dot (CQD) as a donor and a metal organic framework (MOF) as an acceptor, and the donor and the acceptor are connected through a replaceable enzyme response polypeptide bridge; when the fluorescence is complete, FRET is generated to quench the CQD fluorescence, the FRET is interrupted after the target enzyme cuts off the peptide bridge, and the blue / red fluorescence ratio is changed to realize nanomole-level quantitative detection and has self-correction capability. The probe is packaged in a four-arm PEG transparent hydrogel which does not need a photoinitiator and can be quickly self-crosslinked, and can be prepared into a film, a tooth socket and the like for POCT (point-of-care testing) of parts such as an oral cavity / skin and the like. After detection, the MOF is activated by illumination of 630-660 nm to generate active singlet oxygen, so that local antibacterial or anti-tumor treatment is realized, and a diagnosis and treatment integrated scheme is constructed.

The invention provides an oral cavity scanning method, computing equipment and a computer program product. The method comprises the following steps: acquiring first scanning data including three-dimensional data of a scanning rod, an auxiliary feature body and a part of dental arch through an intraoral scanner, and determining a relative position relationship of the scanning rod based on the first scanning data; the method further includes removing three-dimensional data of the scan bar and the auxiliary feature from the first scan data by automated identification, retaining three-dimensional data of a portion of the dental arch, and then acquiring second scan data including the complete dental arch. And synthesizing a three-dimensional image of the oral cavity based on the three-dimensional data of the complete dental arch, the three-dimensional data of the reserved partial dental arch and the relative position relationship of the scanning rods. According to the embodiment of the invention, on the basis of the intraoral scanning technology, the accurate relative position relation between the scanning rods is obtained by using the auxiliary feature bodies, so that the positioning accuracy of the scanning rods is ensured while the scanning process is simplified.

The invention discloses a pronunciation correction data analysis method based on three-dimensional dynamic oral cavity modeling, and relates to the technical field of pronunciation correction, comprising the following steps: performing function fitting on historical reference points to obtain a normal pronunciation function; acquiring a normal pronunciation range based on the normal pronunciation function and the historical reference point; obtaining side views of the tongue part in the three-dimensional oral cavity modeling when the person to be analyzed pronounces and does not pronounce, and respectively marking the side views as a detection pronouncing diagram and a detection non-pronouncing diagram; scaling the detection pronunciation diagram based on the reference size and the detection unpronunciation diagram to obtain a detection correction diagram; judging whether abnormal pronunciation occurs based on the detection correction graph and the normal pronunciation range; the method is used for solving the problem that the accuracy of judging whether the position of the tongue is correct or not during pronunciation is low due to the fact that a method for judging the correct position of the tongue cannot be established through three-dimensional dynamic oral cavity modeling in an existing pronunciation correction technology.

The invention relates to the technical field of oral health management, and discloses an oral health management system based on big data, which comprises a data acquisition module, a data processing module and a data processing module, the intelligent diagnosis module is used for identifying oral health problems and diagnosing oral diseases through deep learning and an artificial intelligence algorithm, the health management suggestion module is used for predicting the future oral health trend of a user based on historical health data according to an intelligent diagnosis result, and the intelligent prediction module is used for predicting the future oral health trend of the user based on the historical health data. And the remote diagnosis and treatment module is used for providing auxiliary services for remote dental diagnosis and treatment. Through a data acquisition module, a data fusion module and an intelligent diagnosis module, oral cavity data and medical image data of a user are integrated, so that formulation of a personalized health management scheme is achieved, personalized oral cavity nursing schemes, diet guidance and living habit adjustment suggestions are provided for each user, and the user experience is improved. Therefore, the accuracy and effect of oral health management are improved.

The invention discloses an intelligent analysis method and system of an oral cavity image, relates to the technical field of image processing, and aims to calculate a tooth deviation index YPZ through intelligent processing and analysis of the oral cavity image and accurately reflect the overall deviation degree of tooth arrangement and occlusion relationship. Through comparison with a preset clinical statistical deviation threshold LZ, an oral suggestion evaluation scheme can be generated, the deviation index and the deviation threshold are iteratively optimized according to feedback information of a patient, in the traditional orthodontic process, a doctor depends on experience and manual judgment, subjective errors may exist, and the adjustment process is lack of a real-time feedback mechanism, so that the accuracy of orthodontic treatment is poor. The lagging of the treatment effect is caused. Through a feedback and adjustment mechanism of the tooth deviation index YPZ and the clinical statistical deviation threshold LZ, dynamic evaluation of the oral health condition and real-time optimization of the treatment scheme are realized by using a back propagation algorithm, and the accuracy and efficiency of the treatment effect are greatly improved.

The invention discloses an oral cavity data monitoring and early warning method and system based on deep learning, and the method comprises the steps: solving a problem that the focus recognition is inaccurate because the image collection process of an oral cavity endoscope of a patient is affected by various environment and equipment parameters; according to the method, synchronous binding of collected images and equipment parameters and intelligent image preprocessing are proposed, historical time sequence images and variation trend features are combined, lesion space and time features are extracted through combination of a lightweight convolutional neural network and a long-short term memory network, feature weighted reasoning is realized by using a context awareness attention fusion network, and the focus space and time features are extracted. According to the method, the model parameters and the risk threshold value can be dynamically adjusted, the focus recognition accuracy and the early warning individuation are improved, and clinical grading treatment and intelligent health management are effectively assisted.

A dental scanning system may include an intraoral scanner and an extraoral imaging device including a color imaging camera couplable in electronic communication with the intraoral scanner. The system may include non-transitory computer readable medium with instructions that, when executed by a processor, cause the system to carry out a method. The method may include capturing 2D image data of a patient's face and teeth with the extraoral imaging device, capturing intraoral 3D image data of a dentition of the patient with the intraoral scanner, generating a 3D model of the patient's teeth based on the intraoral 3D image data, and associating the 2D image data of the patient's face with the 3D model.