4176 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 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.

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 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 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 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 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.

The invention provides a deep learning-based oral cavity image recognition method, a storage medium and a deep learning-based oral cavity image recognition system. The method comprises the steps of deploying a federated learning framework and collecting a multi-modal oral cavity image data set; extracting local features to obtain image features, and generating a modal adaptive weight map; a multi-head self-attention mechanism is used for fusing the cross-modal features to generate a fused feature map, and deconvolution up-sampling is carried out to form high-resolution multi-modal feature representation. A tooth segmentation mask is generated based on this representation, and an initial diagnostic report is generated. And aggregating the attention weight of each client through an encryption protocol, and generating interpretable decision support data. And finally, generating a structured clinical report by using a natural language. According to the method, the Grad-CAM thermodynamic diagram is combined with the encrypted and aggregated attention weight, so that the privacy security is guaranteed, the model interpretability is enhanced, the clinical credibility and the diagnosis decision efficiency are improved, and the problems of insufficient diagnosis precision of complex lesions and insufficient utilization of multi-modal information in the prior art are solved.

The invention relates to the technical field of oral implantation guidance, and provides a digital false tooth mounting and positioning device based on three-dimensional scanning and a method thereof. The method comprises the following steps: scanning the oral cavity of a patient through an oral cavity scanner to generate a three-dimensional oral cavity digital model; generating a virtual implant of the patient and corresponding initial implantation parameters based on the three-dimensional oral cavity digital model through a SegFormer segmentation network; based on historical operation data, initial implantation parameters, bone density, patient attributes and occlusal force parameters, a long sequence prediction network is adopted to predict the position offset and bone resorption degree of the virtual implant after osseointegration through a segmented attention mechanism and a network memory cache mechanism, and optimal implantation parameters are obtained; and pushing a visual dynamic model containing the candidate positioning strategy to the user based on the optimal implantation parameter, driving an oral cavity model printer to obtain an implantation guide plate model and an oral cavity environment model, assisting the user in verifying the installation effect of the candidate positioning strategy, and improving the accuracy of false tooth installation and positioning.

A oral suction device that incorporates a foldable suction body, a bite block and a suction adapter that is utilized to block the throat cavity. The body draws water, saliva and debris from about a gap along its outer perimeter. The suction body resides in a vertical position in the patient's mouth and is able to expand to allow the transport of large pieces of debris without coming apart. There is a fishtail section of the suction body that anchors it between the teeth and the inner cheek so as to allow the remained of the suction body to block the throat hole.

The invention relates to the technical field of three-dimensional point cloud data processing, in particular to a digital denture model design method based on a jaw position relation. Based on comparison of the initial three-dimensional point clouds under different opening amplitudes, a soft tissue interference area where soft tissue movement possibly exists and a hard tissue boundary false displacement area corresponding to point cloud overlapping caused by a scanning view angle are obtained; according to the method, the movement trend of each point in the false displacement area of the hard tissue boundary is corrected in combination with the movement trend of the adjacent area in the oral cavity, so that the corrected three-dimensional point cloud obtained after correction is more accurate, the accuracy of recording according to the corrected three-dimensional point cloud is higher, and the accuracy of the generated digital denture is improved.

The invention discloses an artificial intelligence-based periodontal state evaluation method, which comprises the following steps of: acquiring multi-modal tooth data which comprises a tooth surface image and a local blood vessel network image of an oral cavity; preprocessing the multi-modal tooth data, and performing cross-modal registration by using a registration module to obtain a registered tooth surface image and a registered blood vessel network image; extracting multi-dimensional features of the registered blood vessel network image through a first feature extraction module, wherein the multi-dimensional features comprise spatial morphological features, topological connectivity features and hemodynamic features of blood vessels; extracting macroscopic morphological features and lesion local features of the registered tooth surface image through a second feature extraction module; performing cross-modal fusion on the multi-dimensional features, the macroscopic morphological features, the local lesion features and the clinical data to obtain fusion features; and outputting a periodontal state evaluation result based on the fusion features, thereby facilitating improvement of periodontal state evaluation accuracy and periodontal disease early warning capability.

The invention discloses a precise mark-free positioning system applied to an oral cavity. A camera array composed of a plurality of cameras which are annularly or specifically arranged is arranged on a mobile phone; an infrared imaging assembly for solving the problem of cooling water interference in the operation is designed on at least one camera; the processor is configured to integrate the acquired data including preoperative CBCT (cone beam computed tomography), oral scanning data and digital data of occlusal relationship to construct a complete preoperative oral three-dimensional model; establishing a spatial relationship between a visual system formed by registration of the turbine handpiece and the camera array and a preoperative oral cavity three-dimensional model, and obtaining adaptive relative poses among the parts; after the body position of a patient is fixed during an operation, a complete oral environment point cloud is formed for each frame of input data currently collected by the visual system, and the complete oral environment point cloud is fitted with a patient oral model obtained through oral scanning and CT scanning in advance, so that the oral position of the patient is positioned in real time.

The present disclosure provides a dual-tank oral irrigator. The dual-tank oral irrigator includes a press valve, a first water tank, a second water tank, a water-leading pipe, and a pump assembly. The press valve includes an outlet part, a first inlet part, a second inlet part, and a valve core. The valve core can change its position in the press valve by pressing, so as to seal the first inlet part and the second inlet part. The first inlet part is connected to the first water tank, and the second inlet part is connected to the second water tank. One end of the water-leading pipe is connected to the outlet part. The pump assembly is connected to the other end of the water-leading pipe and a spray-out port of the oral irrigator.

The invention discloses an oral cancer early screening multi-parameter joint detection method and system, and relates to the technical field of data analysis, and the method comprises the steps: obtaining oral multi-dimensional data of a target user; wherein the oral cavity multi-dimensional data of the target user comprises oral cavity image data, oral cavity saliva miRNA data and oral cavity multi-frequency impedance data; presetting an oral cancerization suspicious classification lightweight model, preprocessing the oral multi-dimensional data of the target user, and generating an oral multi-modal feature vector and a preliminary screening oral state classification label of the target user; and deploying a Transform multi-mode oral canceration state grading and classification model, and carrying out conjoint analysis on the oral cavity multi-mode feature vector and the preliminary screening oral cavity state classification label of the target user to generate oral canceration state grading and classification of the target user. The oral canceration recognition method has the advantage that the oral canceration recognition accuracy is improved.

The invention provides a method and device for displaying oral data, computing equipment and a program product. The method comprises the steps that first oral cavity data are obtained, the first oral cavity data comprise three-dimensional data of a dental arch, and the dental arch comprises teeth to be repaired; acquiring second oral cavity data through the intraoral scanner, wherein the second oral cavity data comprises scanning data of the to-be-repaired teeth subjected to tooth preparation processing; identifying tooth regions in the first oral data and the second oral data, and identifying a tooth position of the tooth to be repaired based on a difference between the tooth regions in the first oral data and the second oral data; combining the first oral cavity data and the second oral cavity data based on the identified tooth position of the tooth to be repaired to obtain updated three-dimensional data of the dental arch; and displaying the updated three-dimensional data of the dental arch. In this way, an automated workflow is provided for efficiently generating an oral cavity model containing both a complete dental arch form and a precise tooth preparation form without the need to manually mark a tooth preparation region, thereby improving the accuracy and convenience of oral cavity scanning.

The invention discloses a high-precision and automatic dental crown generation method. The method comprises seven steps of oral cavity three-dimensional data acquisition, full-mouth tooth semantic segmentation, upper and lower jaw point cloud precise registration, abutment and associated gingiva precise segmentation and trimming, abutment surrounding environment multi-tissue segmentation, neck-edge line secondary precise detection, and dental crown generation and multi-dimensional refinement. The method comprises the steps of oral cavity three-dimensional data acquisition, full-mouth tooth semantic segmentation, upper and lower jaw point cloud precise registration, abutment and associated gingiva precise segmentation and trimming, abutment surrounding environment multi-tissue segmentation, neck-edge line secondary precise detection and dental crown generation. Through combination of deep learning and a point cloud algorithm, high-precision segmentation of teeth and gingiva and precise reduction of an occlusion relationship are realized, an oral anatomical feature library and a clinical repair standard are fused, and through multi-dimensional fine adjustment optimization, a dental crown 3D model which is high in fitting degree, harmonious in occlusion and capable of meeting clinical requirements is generated. The method is full-process automatic, greatly improves efficiency, reduces operation threshold, reduces material waste and diagnosis and treatment cost, remarkably improves repair success rate, and is suitable for various oral repair scenes.

The invention belongs to the technical field of three-dimensional point cloud processing, and particularly discloses an automatic tooth segmentation method and system for oral cavity scanning point clouds, and the method comprises the following steps: collecting and preprocessing dentition three-dimensional point clouds, extracting point cloud features containing coordinates and normal directions, and constructing a neighborhood structure; setting a first-stage multi-branch network, and performing tooth and gingiva coarse segmentation and instance initial clustering on the point cloud; setting a second-stage semantic refinement network, and carrying out local cutting on the original point cloud; setting a boundary detection and boundary offset network to enhance a tooth contact area, and refining a boundary instance by clustering to obtain a boundary enhanced instance tag; and performing label fusion, and propagating the fused label to the original high-resolution point cloud through a nearest neighbor algorithm to obtain a final semantic label and a final instance label. By adopting the technical scheme, high-precision instance-level segmentation of the complete dentition point cloud is realized through semantic segmentation, boundary detection and clustering cooperative work based on a biased field.

To provide an image processing apparatus that can more correctly determine a row of teeth having permanent teeth and milk teeth mixed therein.SOLUTION: An image processing apparatus comprises: an acquisition unit that acquires an image of the inside of the oral cavity; an estimation unit that estimates a row of teeth from an image acquired by the acquisition unit by using a learning model that has learned the relationship between the image of the inside of the oral cavity and the row of teeth; and a correction unit that makes a correction on a result of the estimated row of teeth on the basis of a rule related to the order of losing the milk teeth and getting the permanent teeth.SELECTED DRAWING: Figure 4

The dental handpiece has a handle and a housing with a first light-emitting diode and a first optical sensor. The housing also has a second light-emitting diode, a second optical sensor, shielding windows for each optical and apertures for supplying compressed air to each shielding window. A diffuser is located in each aperture, the diffuser being adapted to generate an air jet forming an air curtain. The dental handpiece can provide a reliable protection of the optical sensors by the air curtain and a high-quality three-dimensional image of an oral cavity during manipulation.

A comprehensive and sensuous oral cleaner (10A, 10B, 10C, and 10D) is disclosed to automate and modernize all necessary oral hygiene. The cleaner comprises a power driver (12, 12B, 12C, 12D) that can selectively power-drive a replaceable flosser attachment (13, 14, 15, 17), a replaceable synergistic multi-motion toothbrush attachment (29), and an anti-halitosis attachment (81). The driver also power-drives scent from fragrance sources (68, 24) in the attachments for sensuous ambiance while oral cleaning. The toothbrush attachment is detachably connectable to the power driver for imparting plural motions of a long-bristle toothbrush (77). These actions serve for driving long toothbrush bristles to longitudinally penetrate interdentally for power-brushing interdental contours. In the flosser attachment, a floss span is power-driven in plural motions to efficiently remove plaque as the moving span follows, scrubs, and polishes interdental contours between adjacent teeth. Three embodiments of the flosser attachment use warmed power-driven air to dry the used floss for odor-free storage until replacement of the attachment. Alternatively, two of the flosser attachment embodiments feature an antimicrobial (68) that coats the used floss to inhibit microbial activity. The power-driven anti-halitosis attachment drives a multi-bladed tongue scraper (89, 89B) along with pressurized air to neutralize causal anaerobic tongue bacteria.

The invention provides an implant immediate denture precise manufacturing system based on preoperative planning and three-dimensional registration. An example method includes obtaining first oral data, the first oral data including three-dimensional data of a denture model and three-dimensional data of a marker; acquiring second oral cavity data, wherein the second oral cavity data comprises scanning data of a plurality of bases fixed in the oral cavity and a marker; registering the first scanning data and the second scanning data based on the matching of the three-dimensional data of the marker and the scanning data of the marker; a denture model to be processed is generated based on a result of the registration, the denture model to be processed comprising three-dimensional data of the denture model and positioning information of a plurality of holes, each hole being for accommodating one of the plurality of abutment. According to the embodiment of the invention, the accurate positioning of the false tooth model and the abutment is realized by using a digital technology, the accurate matching of the false tooth and the abutment is ensured, and the comfort and experience of a dental implant patient are improved.

The invention relates to the field of oral cavities, and particularly discloses a lasting antibacterial type composite tooth socket for medicine carrying and a preparation method thereof.The lasting antibacterial type composite tooth socket comprises an adsorption layer and an antibacterial membrane layer, the adsorption layer is used for adsorbing oral cavity treatment liquid medicine, and the antibacterial membrane layer comprises a nano-silver antibacterial layer and a chitosan antibacterial layer; the preparation method comprises the following steps: mixing a tea polyphenol-polylactic acid composite solution, a nano-silver-carboxylation modified cellulose compound and a polyvinyl alcohol solution, and carrying out electrostatic spinning to prepare a nano-silver antibacterial fiber membrane, so as to form the nano-silver antibacterial layer; mixing chitosan with hot water, adding cinnamyl aldehyde, glycerol and boric acid, stirring to obtain a mixed solution, coating one side of the nano-silver antibacterial layer with the mixed solution, and curing to form a chitosan antibacterial layer; the adsorption layer is attached to the side, away from the chitosan antibacterial layer, of the nano-silver antibacterial layer, and then the lasting antibacterial type composite tooth socket for carrying the medicine is prepared through hot-pressing compounding. The drug-loaded composite tooth socket has the characteristic of further improving the antibacterial property and the antibacterial durability of the drug-loaded composite tooth socket.

This invention represents a marked improvement in pediatric oral hygiene, especially focusing on the vital early stages of an infant's oral development. Offering a versatile, easy-to-use device from the onset of an infant's life, the present device lays the groundwork for robust oral health, significantly reducing the risk of future dental issues. The unique design, combined with its adaptability and effectiveness in early oral care, makes it an indispensable tool in fostering comprehensive oral hygiene from infancy, thereby contributing to the lifelong dental well-being of individuals.

The invention relates to an oral implant positioning method and system based on deep learning. According to the method, three-dimensional point cloud data of an oral cavity is obtained and preprocessed, and a pre-trained three-dimensional deep learning segmentation model is utilized to automatically and accurately segment tooth, gingiva and alveolar bone structures. And based on the segmentation result, extracting key form and spatial relationship characteristics of the alveolar bone, and matching with an implant database to primarily select a candidate scheme. By integrating geometric constraint verification and biomechanical simulation, the candidate schemes are optimized and decided, and the optimal implant implantation position and posture meeting the safety and biomechanical requirements are calculated. And finally, automatically generating digital operation guide plate data completely matched with the gingival form of the patient according to the optimal scheme. According to the method, automation and intellectualization of the whole process from data collection to surgical guide plate generation are achieved, the defects that a traditional method depends on artificial experience, is high in subjectivity and low in efficiency are effectively overcome, and the precision, efficiency and reliability of implantation surgical planning are remarkably improved.

The invention discloses a stomach tube tail end three-dimensional positioning method based on a high-precision permanent magnet mark and a flexible TMR array. The method comprises the following steps: disinfecting a stomach tube and a permanent magnet marker; the miniaturized permanent magnet marker is firmly installed at the front end of the stomach tube; reserving a mounting position at the front end of the stomach tube, and inserting the stomach tube into the esophagus of a patient through a nasal cavity or an oral cavity until the stomach tube reaches a preset position; flexible TMR sensor arrays in double-sided distribution are arranged in the chest area and the back area of the patient; according to magnetic field data detected by a TMR sensor array, coordinates of a permanent magnet marker in a sensor coordinate system are solved through magnetic dipole modeling and nonlinear optimization, a thoracic coordinate system transformation matrix is established, and three-dimensional position coordinates of the permanent magnet marker in a world coordinate system are determined; a magnetic dipole reverse solution positioning method is adopted, and meanwhile, the zero radiation exposure risk is ensured; spatial registration with an ultrasonic image is supported, and the positioning precision and the anti-interference capability are improved.

The invention relates to the field of oral clinical orthodontics, and discloses a method for generating an oral correction scheme, comprising: acquiring a face composite model of an initial state of a patient, the face composite model comprising a dental jaw portion and a soft tissue portion; respectively obtaining P correction schemes of the patient, wherein each correction scheme corresponds to a target state of tooth jaw movement; correspondingly obtaining face prediction models of P target states according to the tooth jaw movement and deformation face composite models of the P correction schemes; and in the P correction schemes, selecting an optimal correction scheme as a target correction scheme according to evaluation of the face prediction model in the target state. The invention further discloses electronic equipment and a storage medium, the orthodontic scheme is determined by predicting the appearance, the predicted result is closer to the real effect after orthodontic treatment, more bases are provided for the patient to select the orthodontic scheme, the patient can conveniently determine the ideal orthodontic scheme from the face expression, and a more preferable orthodontic scheme is generated.

The invention discloses a variable convolution UNet tooth image segmentation method and system fusing an attention mechanism, and belongs to the technical field of medical image processing and computer-aided diagnosis. A tooth image data set is obtained and preprocessed; using the preprocessed data set to train a DSC-UNet segmentation model; the DSC-UNet segmentation model introduces a multi-modal feature fusion module and a deformable convolution module into a UNet framework; and segmenting an input tooth image by using the trained DSC-UNet segmentation model, and outputting a pixel-level segmentation result of the tooth structure. By constructing a multi-level feature interaction mechanism and a deformable convolution module, the capturing capability of the network on tooth edge details and the segmentation robustness of special-shaped teeth are remarkably improved, more reliable technical support is provided for an intelligent dental diagnosis and treatment system, and the method is particularly suitable for high-precision segmentation of complex tooth structures in oral panoramic X-ray films and CBCT images.