33 results about "Single tooth implant" patented technology

The invention discloses a tooth instance segmentation method and device based on anatomic form priori, and belongs to the field of computer vision and artificial intelligence. According to the method, model training is carried out on a CBCT image, a real segmentation mask is processed into a three-classification segmentation mask with enamel as a boundary, the three-classification segmentation mask serves as a supervision signal, a network can directly output a prediction segmentation mask containing tooth boundary information in a reasoning stage, and a detection frame is generated accordingly. And after the detection frame is scaled according to the same proportionality coefficient and projected back to the original image, cutting each tooth to obtain a CBCT image of the single tooth. A loss function based on anatomical morphological prior is introduced into segmentation training of a single tooth CBCT image, and a network is constrained through a self-adaptively extracted morphological skeleton, so that a prediction segmentation mask is kept continuous at a root tip part, and the problem of tooth root segmentation fracture is effectively relieved. According to the method, accurate positioning and high-quality segmentation of the tooth instances are realized, so that the segmentation of the tooth instances in the full-mouth CBCT image is quicker and more accurate.

Embodiments of the present invention provide a method, system, devices and software which provide customized, clinically relevant designs, e.g. treatment plans / solutions for at least single tooth replacement therapy in real-time as needed to enable immediate confirmation of the validity and execution of patient-specific treatment solutions.A Machine Learning algorithm is used in a method or system for computer implementation of automatic restoration design. The restoration design includes the design of restorative elements such as crowns and abutments. Software is provided for carrying out the methods when executed on a digital processor. Manufacturing of the restorative elements is also included.

The invention discloses an IOS image and CBCT image registration method based on particle swarm and single-tooth optimization, and belongs to the field of image data processing, and the method comprises the following steps: respectively obtaining tooth semantic segmentation results and point cloud data of an IOS image and a CBCT image through preprocessing and segmentation steps; introducing a particle swarm optimization algorithm, and performing iterative search and optimization on six-degree-of-freedom rigid transformation parameters between the IOS image data and the CBCT image data so as to complete global initial registration of the dental arch scale; and on the basis of a result after global registration, a registration object is divided into a plurality of local units based on a single tooth, and local iteration alignment is performed on each unit, so that tiny dislocation on the single tooth is eliminated, and the overall registration effect is optimized. According to the method, on the basis of processing cross-modal difference and realizing global registration, the registration precision of a single tooth level is further ensured through a local optimization mechanism, and reliable automatic registration support is provided for clinical scenes such as orthodontics and implantation.

This invention relates to the interdisciplinary field of medical image analysis and artificial intelligence, and particularly to a method, device, and medium for detecting non-occlusal abnormalities based on oral images. The method first acquires oral images and determines their abnormality category: a first abnormality (dependent on the characteristics of a single tooth) or a second abnormality (dependent on the spatial relationships between multiple teeth). Based on the category determination, an adaptive differential detection process is executed: if it is a first abnormality, a two-stage process of tooth position detection and single-tooth recognition is used to output a detection result associated with a precise FDI number; if it is a second abnormality, an end-to-end target detection model directly outputs the abnormality type and location region; if it is a mixed category, the two processes are executed in parallel and the results are intelligently integrated. This invention achieves automated, precise, and structured detection of non-occlusal diseases.

This invention belongs to the field of medical image processing technology and proposes a method for 3D tooth point cloud segmentation and tooth type recognition based on deep learning. The main scheme is as follows: acquire 3D tooth point cloud data, construct a 3D tooth point cloud dataset and perform data preprocessing; construct a 3D tooth point cloud semantic segmentation network and determine the loss function, and train the 3D tooth point cloud semantic segmentation network based on the loss function; use the trained 3D tooth point cloud semantic segmentation network to perform point-by-point semantic prediction on the point cloud of the tooth row to be tested, and obtain the point-level category probability distribution; perform multi-level probability smoothing and interpolation recovery on the point-level category probability distribution to improve the spatial continuity of the prediction results and restore the original point cloud resolution; perform density-adaptive connectivity analysis and denoising processing on the restored point cloud segmentation results to extract single tooth instances; and use instance-level category statistics for each single tooth instance to determine the final semantic category, thereby realizing tooth type recognition.

An automated method for aligning a 3D single tooth model to 3D oral scan data includes determining an oral scan landmark and a teeth curve formed by teeth in the 3D oral scan data, determining a margin line of a target tooth in the 3D oral scan data and a region of interest in the 3D oral scan data, determining first to third axes of the 3D oral scan data in the region of interest based on the oral scan landmark, determining a single tooth landmark of the 3D single tooth model, determining fourth to sixth axes of the 3D single tooth model based on the single tooth landmark and aligning the 3D single tooth model to the 3D oral scan data such that the fourth to sixth axes of the 3D single tooth model respectively overlap the first to third axes of the 3D oral scan data.

The present invention relates to an image processing method, comprising: acquiring a visible light image, a near-infrared image, and a fluorescence image of the same tooth region to obtain a multimodal image; inputting the multimodal image into a segmentation network, wherein a spatial attention module is embedded in the skip connection between the encoder and decoder of the segmentation network, and the segmentation network outputs a binary mask of the tooth region; extracting the contours of individual teeth from the binary mask, determining the minimum bounding rectangle and geometric center of gravity of each contour; assigning an FDI tooth position code to each contour based on the horizontal coordinate of the geometric center of gravity; cropping the corresponding individual tooth image block from the multimodal image based on the minimum bounding rectangle; inputting the individual tooth image block into a multi-branch convolutional neural network to obtain a unified feature vector; inputting the unified feature vector into a fully connected classification network, which outputs probability values ​​corresponding to different categories. The present invention also relates to image processing devices, media, computer program products, and tooth recognition systems.

This invention discloses a method for registering IOS and CBCT images based on particle swarm optimization and single-tooth optimization, belonging to the field of image data processing. The method includes the following steps: Preprocessing and segmentation steps are used to obtain the semantic segmentation results of teeth from IOS and CBCT images, as well as point cloud data; a particle swarm optimization algorithm is introduced to iteratively search and optimize the six-degree-of-freedom rigid transformation parameters between the IOS and CBCT image data, thereby completing the initial global registration at the dental arch scale; using the globally registered result as a basis, the registration object is divided into multiple local units based on a single tooth, and local iterative alignment is performed on each unit to eliminate minor misalignments on individual teeth and optimize the overall registration effect. This invention, based on handling cross-modal differences and achieving global registration, further ensures registration accuracy at the single-tooth level through a local optimization mechanism, providing reliable automated registration support for clinical scenarios such as orthodontics and implantology.

The application provides a tooth segmentation method and device in an image. The method comprises the following steps: acquiring a plurality of cross-sectional images of teeth, and determining a connected domain of each cross-sectional image; if a target connected domain of a current cross-sectional image comprises pixels of a plurality of connected domains of a previous cross-sectional image, it is determined that the target connected domain appears bifurcation intersection; performing corrosion processing on the target connected domain to obtain a final cross-sectional image; and performing tooth segmentation processing based on the final cross-sectional image. In this way, the problem of tooth data adhesion in single tooth positioning can be solved by judging whether the connected domain appears bifurcation intersection, and the accuracy of tooth segmentation and positioning is improved.

The application discloses a force couple orthodontic accessory, a personalized fixed appliance, a tooth correction system, a design method of the force couple orthodontic accessory and a design method of the tooth correction system. The force couple orthodontic accessory comprises a bottom plate, an accessory body and a force couple structure, the bottom plate is used for being bonded with a labial buccal surface of a tooth, the accessory body is provided with an arch wire accommodating cavity, and the force couple structure is arranged in the arch wire accommodating cavity and comprises protrusions and / or grooves which are symmetrically arranged on both sides of the channel and are used for cooperating with partial bending structures of an arch wire to form a force couple for a single tooth. The personalized fixed appliance comprises a plurality of force couple orthodontic accessories and a personalized arch wire, the arch wire is provided with partial bending structures corresponding to positions of teeth to be corrected, and a preset force couple is formed after loading. The force couple orthodontic accessory, the personalized fixed appliance and the tooth correction system provided by the application realize accurate force couple control of a single tooth and improve correction precision and a personalized degree.

The application relates to a gum edge line generation method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring a single tooth edge line to obtain a tooth gum edge line; calculating a gum contour line according to the tooth gum edge line, and calculating a gum edge line according to the gum contour line; and updating the gum edge line according to a tooth displacement data table to obtain an updated gum edge line. The method can automatically cut a tooth corrector, improve the production efficiency of the tooth corrector and reduce the production cost. Meanwhile, the application improves the precision of gum edge cutting of the tooth corrector, so that the gum is not damaged when a user wears the tooth corrector, and the comfort of the user wearing the tooth corrector is improved.

The present invention provides an intelligent surgical planning method and system for autologous tooth transplantation, relating to the field of image processing technology. The method comprises: obtaining a CBCT image of a tooth to be operated on; segmenting each individual tooth in the CBCT image using a 3D UX‑Net network; segmenting the upper and lower jaws in the CBCT image using a SegResNet network; determining various feasible transplantation surgical planning schemes for transplanting an alternative donor tooth to a recipient tooth using principal component analysis based on the segmentation results of the individual teeth and the jaw; and determining the optimal transplantation surgical planning scheme based on the crown overlap rate, root overlap rate, and amount of bone grinding between the recipient and donor teeth in various transplantation surgical planning schemes. The method achieves precise segmentation of individual teeth and the upper and lower jaws; effectively controls the amount of bone grinding and optimizes the matching between the donor and donor teeth, thereby improving the surgical success rate and postoperative comfort.

The application provides a tooth digital model posture deviation calculation method, system, scoring method and terminal, the calculation method comprises the following steps: selecting a single tooth model in a tooth digital model, establishing a local coordinate system on the single tooth model, and obtaining feature points of the single tooth model in the local coordinate system; a global coordinate system is established according to the tooth digital model, the feature points are converted from the local coordinate system to the global coordinate system, and first feature points in the global coordinate system are obtained; the points with a distance less than a first threshold value from the first feature points are taken as tooth arch corresponding points on a tooth arch curve of the tooth digital model, a tooth arch coordinate system is established by taking the tangent direction, the normal direction and the jaw plane direction of the tooth arch corresponding points as three axes; model posture parameters are calculated according to the first feature points, the tooth arch corresponding points and the tooth arch coordinate system, and a posture result of the tooth digital model is calculated according to the model posture parameters, and the calculation method effectively improves the processing efficiency and accuracy of the posture result calculation of the tooth digital model.

The present application relates to a kind of orthodontic process monitoring methods based on dentition three-dimensional model prediction in the technical field of orthodontics, comprising the following steps: a kind of orthodontic process monitoring methods based on dentition three-dimensional model prediction, characterized by comprising the following steps: S1, obtain the three-dimensional dental model data of T n Moment and segmentation processing, output the mask and corresponding tooth number of single tooth in three-dimensional dental model;S2, obtain the two-dimensional image data of N teeth of T n+m Moment and segmentation processing, output the mask and corresponding tooth number of single tooth of two-dimensional tooth;S3, reference point detection: including by immovable tooth prediction and manual marking;S4, camera pose estimation: S5, tooth pose estimation: S6, dentition three-dimensional reconstruction.The present application realizes the accurate estimation, monitoring of moving tooth in orthodontic treatment process by the prediction of dentition three-dimensional model at different time in orthodontic process, can effectively assist orthodontic scheme to smoothly carry out.

The application discloses a structure of a fence type indirect bonding guide plate with a removable cover, a manufacturing method and application, and belongs to the technical field of oral fixed orthodontics. The application obtains a three-dimensional data model by scanning, adopts a guide plate design software, determines the bracket position of each tooth on the three-dimensional data model, designs an element for positioning the single-tooth bracket position, specifically designs the structure of the removable cover, single-axis movement and the breakable horizontal fence of the element, copies the element on each tooth position on the three-dimensional data model, connects the elements of each tooth position through a connecting piece, completes the design of the indirect bonding guide plate, and adopts 3D printing to manufacture the finished product. The indirect bonding guide plate has the advantages of easy positioning, no undercut, easy removal of the excess bonding agent, and difficulty in removing the bracket when dislocation, and is a global oral field exploration topic and a future development direction of oral diagnosis and treatment, represents the top level of modern digital medical technology, and makes oral fixed orthodontic treatment more scientific, accurate and convenient.

The application discloses a tooth segmentation method, a tooth surface data acquisition method, a storage medium and an oral CT device. The tooth segmentation method comprises the following steps: acquiring an oral CT image to be segmented; positioning a whole tooth region in the oral CT image to be segmented by using a first neural network which is pre-trained; positioning a single tooth region of a preset range in the whole tooth region by using a second neural network which is pre-trained; and performing mask segmentation on the single tooth region by using a third neural network which is pre-trained, so as to obtain tooth data of a corresponding tooth. Therefore, the tooth segmentation method can realize effective and accurate segmentation of teeth in the oral CT image.

The application relates to a method for manufacturing an expander and a hidden orthodontic device, and relates to the technical field of oral orthodontics. A single-tooth digital dental model is obtained based on a digital dental model, and a vertical height of a top of a palate and a bite plane is obtained based on the single-tooth digital dental model, a connecting position of the expander and the device is determined, a digital expander model is obtained based on a software method, the obtained digital expander model has strong technical universality, does not need to excessively depend on personal experience, and the manufactured expander is more comfortable to wear.

This invention provides a method for tooth image segmentation, a storage medium, and an electronic device. The method includes the following steps: S1: acquiring a dental model image; S2: inputting the dental model image into a trained first neural network, outputting vector information corresponding to the feature points of the teeth in the dental model image; S3: performing cluster analysis on all the vector information, filtering out several vector information sets, and determining the corresponding tooth center point coordinates based on the vector information in each set; S4: segmenting the dental model image based on the coordinates of each tooth center point to obtain a segmented tooth image. This solution, by first obtaining the vector information corresponding to the feature points on the teeth, then performing cluster analysis based on all the vector information to obtain the center point coordinates of each tooth in the dental model image, and finally completing the identification and segmentation of a single tooth based on the center point coordinates, can effectively improve the accuracy of tooth image segmentation.

Embodiments of the present invention provide a method, system, devices and software which provide customized, clinically relevant designs, e.g. treatment plans / solutions for at least single tooth replacement therapy in real-time as needed to enable immediate confirmation of the validity and execution of patient-specific treatment solutions. A Machine Learning algorithm is used in a method or system for computer implementation of automatic restoration design. The restoration design includes the design of restorative elements such as crowns and abutments. Software is provided for carrying out the methods when executed on a digital processor. Manufacturing of the restorative elements is also included.

The application discloses a portable full-wrapping caries detection device and system based on multi-modal optics; the device comprises a handheld part for handheld use, a first telescopic part, a second driven part and a third connecting part, a probe head is arranged at the other end of the third connecting part, a driven sliding ring capable of slidingly adjusting a position is inlaid at the inner side of the probe head, a plurality of detection parts for detecting teeth are uniformly arranged at the inner side of the driven sliding ring; the application discloses a full-wrapping detection configuration which is constructed by arranging a C-shaped or U-shaped probe head and a driven sliding ring capable of rotating at the inner side of the probe head, and the traditional single-shaft rigid straight handle probe is abandoned; when the probe is clamped, the plurality of detection parts distributed at the inner side of the driven sliding ring can simultaneously form a "three-surface synchronous" wrapping of a single tooth from the occlusal surface, the buccal side and the lingual side, three-dimensional dead angle-free detection is realized, and the detection rate of early interproximal caries is greatly improved.

The application discloses an oral scanning tooth position recognition system and method based on artificial intelligence, relates to the technical field of digital oral cavity, and comprises data acquisition, pretreatment, feature extraction and segmentation, tooth position recognition, result output and model training modules. The feature extraction adopts a deep learning network fusing local and expanded features, extracts local geometric features through dynamic edge convolution, and extracts long-distance semantic features by combining expanded edge convolution and hybrid sampling. The method processes oral scanning data through the above modules, realizes gingival segmentation, single tooth division and tooth position recognition, outputs segmentation masks and recognition results, and improves recognition accuracy and efficiency.

The invention discloses a two-stage multi-task oral cavity CBCT image segmentation method, and belongs to the technical field of oral medical image segmentation, and the method comprises the steps: obtaining an in-oral cavity CBCT image, and carrying out the preprocessing; a medical image segmentation model nnUNet is adopted as a basic network to carry out first-stage multi-structure segmentation training on a CBCT image, and metal artifacts are removed; designing a dual-output multi-task learning network W-UNETR to carry out a second stage of tooth segmentation and quadrant classification; designing a parallel space-channel attention module PSCA-SE for the 3D medical image data for feature enhancement; constructing a multi-task loss function and a learning rate strategy until the loss function converges; and evaluating the performance of the model by adopting Dice similarity coefficients DSC and HD95. According to the method, through a two-stage multi-task segmentation strategy, the feature extraction capability is enhanced in combination with PSCA-SE, the segmentation precision is improved in cooperation with a DiceCELoss multi-task loss function, user interaction selection of ROI is supported to obtain a complete single tooth, and efficient and accurate oral cavity CBCT image segmentation is realized through DSC and HD95 accurate evaluation.

The invention relates to the technical field of image recognition, in particular to a periodontitis staging diagnosis auxiliary method based on deep learning, which comprises the following steps: acquiring a panoramic dental film image of a patient and preprocessing the panoramic dental film image to obtain a preprocessed image; segmenting the preprocessed image by adopting a semantic segmentation model to obtain a maxillofacial region; identifying the maxillofacial region by adopting a mask segmentation model to obtain a mark position of each tooth; and generating an RBL value of each tooth according to the mark position and outputting a key region of interest. In order to solve the problem that in the prior art, a technical scheme of adopting a model to directly learn periodontitis characteristics to carry out auxiliary recognition is poor in interpretability in the diagnosis process, in the scheme, a maxillofacial region is sequentially segmented through different models to obtain single teeth, a specific mark position is extracted for each tooth, and the identification accuracy is improved. The RBL value is calculated in combination with the pixel coordinates, point locations worthy of attention are screened, the processing flow is high in interpretability, and more reference information can be provided for doctors.

The invention relates to the technical field of image recognition, and provides a two-stage full-mouth focus detection method and system, electronic equipment and a medium, and the method comprises the following steps: obtaining an oral CT image, processing the oral CT image through a pre-trained target detection model, positioning and detecting a single tooth, and obtaining a single tooth region image; utilizing the target detection model to continuously identify each single tooth area image to obtain the position and the category of a focus area; wherein a loss function adopted by the target detection model in the training process is formed by weighting a position loss function, a classification loss function and a target confidence loss function. According to the method, the single tooth is firstly positioned, then the focus area is finely identified, the multi-task weighted loss function is combined, the position, the classification and the confidence coefficient are optimized, and the accuracy and the robustness of small focus detection are remarkably improved.

The invention provides a mounting table of a shell-shaped tooth appliance traction device and a design method of a dental instrument.The traction device mounting table is applied to a shell-shaped tooth appliance, the traction device is fixed to the traction device mounting table, and the design method of the mounting table comprises the steps that the center point of a single tooth model is selected; projecting the central point of the single tooth model to the target dental arch curve to obtain a projection point corresponding to the single tooth model; establishing a normal direction perpendicular to the tangent plane of the surface of the corresponding single tooth model according to the corresponding projection point, setting the height of a normal bulge, and establishing a mounting table reference point and a long axis direction of the mounting table; designing an angle between the mounting surface and a dental arch curve section of a corresponding accommodating tooth; and designing a complete structure of the mounting table. The dental instrument provided by the invention can perform angle compensation according to the traction direction of the traction device, so that the stress of the dental instrument is more consistent with a correction plan during traction correction, and the correction accuracy is improved.

The invention relates to the technical field of tooth key point detection, and discloses a tooth key point positioning method and device based on a mouth scanning three-dimensional model, and the method comprises the steps: determining tooth data of a to-be-detected object based on a predetermined mouth scanning three-dimensional model; preprocessing the tooth mesh data of each tooth position through a first type processing module to obtain point cloud data; generating tooth position related data of each tooth position through a second type processing module of the trained key point detection model according to the tooth position number of each tooth position and preset tooth position conversion rule information; and carrying out fusion processing on the point cloud data of each tooth position and the tooth position related data through a third type processing module of the key point detection model so as to detect the key point coordinates of the single tooth corresponding to the tooth position. Therefore, all tooth key points of the to-be-detected object can be detected through one key point detection model, and the key point detection efficiency and detection accuracy can be improved.

The application relates to a manufacturing method of an integrated post core based on a single tooth impression, an integrated post core and a post core system, and relates to the technical field of dental post core repair. The method can solve the problems of poor post core positioning and poor suitability. The method comprises the following steps: performing tooth preparation on a diseased tooth according to the requirements of full crown repair, and performing root canal post channel preparation on the diseased tooth by using a reaming drill; performing a single tooth impression on the diseased tooth to obtain a post core impression of the diseased tooth, scanning the post core impression of the diseased tooth to obtain a digital single tooth impression, and then performing intraoral dentition scanning on the patient; performing digital design and processing and manufacturing of the integrated post core according to the digital single tooth impression and the intraoral dentition scanning result, to obtain an initial integrated post core; performing model trial fitting and adjustment on the initial integrated post core to obtain a target integrated post core, and performing clinical trial fitting and adhesion on the target integrated post core.

This application discloses a method, apparatus, device, medium, and product for detecting dental defects in children, relating to the field of image processing technology. The method includes preprocessing an acquired panoramic radiograph of a child to be detected to obtain a standard image of a child's teeth; extracting local and global feature vectors from the standard image of the child's teeth, and then weighted and fused the extracted local and global feature vectors to obtain a fused feature image of the teeth; extracting geometric anchor points and calibrating the coordinates of each tooth region based on the fused feature image of the teeth to obtain the positional information of each tooth; matching the defect type of a single tooth region according to the fused feature image of the teeth and the positional information of each tooth to obtain a defect identification result; and generating a detection result based on the defect identification result and the positional information of each tooth. This application improves the detection accuracy and positioning precision of permanent and deciduous teeth in children on panoramic radiographs, avoiding missed detection of small teeth.

The invention relates to a decayed tooth identification method based on an oral panoramic image, a training method, a device, equipment, a medium and a program product. The method comprises the following steps: obtaining an oral panoramic image, and obtaining each to-be-processed single tooth image of each single tooth based on the oral panoramic image; performing semantic segmentation on each to-be-processed single tooth image through a pre-trained semantic segmentation model to obtain each first decayed tooth recognition result corresponding to each to-be-processed single tooth image; obtaining each target single tooth image of the decayed tooth represented by the first decayed tooth identification result from each single tooth image to be processed; and processing based on the masks corresponding to the target tooth masks and the oral panoramic image, and obtaining a decayed tooth classification result through a pre-trained decayed tooth classification model. The caries identification accuracy can be improved by adopting the method.

The application discloses a tooth instance segmentation method and device based on anatomical morphology prior, and belongs to the field of computer vision and artificial intelligence. The method trains a model on a CBCT image, processes a real segmentation mask into a three-class segmentation mask with enamel as a boundary as a supervision signal, enables the network to directly output a predicted segmentation mask containing tooth boundary information in an inference stage, and generates a detection frame according to the predicted segmentation mask. The detection frame is scaled by the same proportional coefficient and projected back to the original image, and each tooth is cut to obtain a single tooth CBCT image. In the segmentation training of the single tooth CBCT image, a loss function based on anatomical morphology prior is introduced, the network is constrained by an adaptively extracted morphological skeleton, the continuity of the predicted segmentation mask at the root tip part is promoted, and the tooth root segmentation fracture problem is effectively alleviated. The method realizes accurate positioning and high-quality segmentation of tooth instances, and makes the tooth instance segmentation in a full-mouth CBCT image more rapid and accurate.