CN109875684A - A kind of prediction and real-time rendering method of mandibular angle bone cutting art - Google Patents

A kind of prediction and real-time rendering method of mandibular angle bone cutting art Download PDF

Info

Publication number
CN109875684A
CN109875684A CN201910305894.8A CN201910305894A CN109875684A CN 109875684 A CN109875684 A CN 109875684A CN 201910305894 A CN201910305894 A CN 201910305894A CN 109875684 A CN109875684 A CN 109875684A
Authority
CN
China
Prior art keywords
mandibular
preoperative
danger area
patient
real
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201910305894.8A
Other languages
Chinese (zh)
Inventor
薛红宇
张颂
蔡辉
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Peking University Third Hospital Peking University Third Clinical Medical College
Original Assignee
Peking University Third Hospital Peking University Third Clinical Medical College
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Peking University Third Hospital Peking University Third Clinical Medical College filed Critical Peking University Third Hospital Peking University Third Clinical Medical College
Priority to CN201910305894.8A priority Critical patent/CN109875684A/en
Publication of CN109875684A publication Critical patent/CN109875684A/en
Priority to CN202010209824.5A priority patent/CN111227933B/en
Pending legal-status Critical Current

Links

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10Computer-aided planning, simulation or modelling of surgical operations
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/20Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10Computer-aided planning, simulation or modelling of surgical operations
    • A61B2034/101Computer-aided simulation of surgical operations
    • A61B2034/105Modelling of the patient, e.g. for ligaments or bones
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/20Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
    • A61B2034/2046Tracking techniques
    • A61B2034/2065Tracking using image or pattern recognition

Landscapes

  • Health & Medical Sciences (AREA)
  • Surgery (AREA)
  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Robotics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Dental Tools And Instruments Or Auxiliary Dental Instruments (AREA)

Abstract

The invention discloses a kind of prediction of mandibular angle bone cutting art and real-time rendering methods, the following steps are included: S1, the preoperative CT image according to mandibular angle bone cutting patient with operation, the lower denture rivet point of mandibular angle bone cutting patient with operation, danger area are obtained, and demarcates maximum and bones range;S2, range that the preoperative CT image of mandibular angle bone cutting patient with operation, preoperative photo, prediction postoperative film, maximum are boned, input osteotomy surface prediction model, the amputation line of actual patient, face of boning are predicted, in conjunction with AR equipment, real-time rendering visual area amputates line, face of boning, danger area.The present invention carries out real-time rendering to the visual area of actual patient, improves operation precision, reduce operation risk, shorten operating time, reduce postoperative complication according to the preoperative CT, preoperative photo and osteotomy surface prediction model of actual patient.

Description

A kind of prediction and real-time rendering method of mandibular angle bone cutting art
Technical field
The present invention relates to mandibular angle bone cutting art technical field, prediction more particularly, to a kind of mandibular angle bone cutting art and in real time Rendering method.
Background technique
Due to the variation of mandibular angle bone cutting postoperative patient facial appearance, remove with Mandible Osteotomy amount phase outside the Pass, it is soft with part Also some association of the variation of soft tissue volume amount caused by tissue tension changes.Therefore, mandibular angle bone cutting art goes bone amount It is not to do subtraction between pre-operative patients facial appearance and Estimating the result, is previously scanned by means of three dimensional CT and face 3D merely Photographic system carries out the 3D design of surgical effect, can not Accurate Prediction reach postoperative prediction in mandibular angle bone cutting art and imitate Angle of mandible removes bone amount and osteotomy surface morphologic localization when fruit.
The existing operation guiding system for mandibular angle bone cutting art, by carrying out CT scan to patient, and by shadow As data are rebuild and are handled, osteotomy line is designed by the past clinical experience, and be labeled in the three-dimensional data of mandibular On model, osteotomy line is subdivided into multiple brill points by robot perceptual system, by carrying out many places along osteotomy line on bone face Point drilling is bored to realize osteotomy.Meanwhile the system marks complex by being formed in lower jaw angular region drilling linkage flag module, or Facing mould is customized according to denture form under patient, and mark module is connected on facing mould, is connected in art by patient-worn The facing mould of mark module judges the relative position of mandibular.In art, system is by augmented reality by distinguishing label Module judges mandibular relative position, and determines osteotomy line position, passes through RAS row mandibular angle bone cutting art to realize.The operation is led Boat system passes through clinical practice application, and mean error is smaller, it is ensured that the safety of operation, while in auxiliary doctors experience product It is tired etc. to have stronger advantage.But presently, there are three shortcomings for the system: (1) needing additional fixed signal point: by advising Patient-worn is connected with the facing mould of mark module to determine osteotomy line, since connection type is non-rigid connection, gets the bid in art Remember that there are the risks of higher relative shift between module and mandibular, there are errors so as to cause the judgement of osteotomy line, reduce Operation safety;Or mark module is connected to lower jaw angular region by bore mode, though mark module is greatly improved under The stability of relative positional relationship between jawbone body, but since the mandibular angle bone cutting art actual operation operating space of intra-oral approach is narrow And it is deep, operation of fixation mark module difficulty itself is higher, while mark module is excessively huge with respect to visual area, can be realized properly The applicable case for placing mark module is greatly limited.(2) operation guiding system is for the processing of osteotomy mode Using the mode of mechanical interruption punching, due to the duct through bone tissue that punching is formed be it is linear, this mode for It needing to carry out the case of mandibular osteo-distraction removal art simultaneously and is not suitable for, the osteotomy surface formed is a flat surface and non-curved, Largely limit the application range of the operation guiding system.(3) operation guiding system is not to mandibular angle bone cutting art Soft tissue change afterwards is paid attention to, the past experience of osteotomy line designed completely by patient, and no quantization index, this is Although system improves the safety of operation, Accurate Prediction patient postoperative effect and raising patient satisfaction etc. are had no Advantage.
Therefore, a kind of operation for mandibular angle bone cutting art based on artificial intelligence technology and augmented reality is designed to lead Boat system, the osteotomy amount prediction technique of the whole operation designing mandibular angle bone cutting art that assists a physician, is current urgent problem to be solved.
Summary of the invention
The object of the present invention is to provide a kind of osteotomy amount prediction techniques of mandibular angle bone cutting art, by predicting mould in osteotomy surface Preoperative CT image data set, preoperative picture data collection, the postoperative simulation picture data of mandibular angle bone cutting patient with operation are inputted in type Collection obtains the osteotomy surface of mandibular angle bone cutting patient with operation.
Foregoing invention purpose of the invention is achieved by the following technical programs:
A kind of prediction and real-time rendering method of mandibular angle bone cutting art, comprising the following steps:
S1, the preoperative CT image according to mandibular angle bone cutting patient with operation obtain the lower denture rivet of mandibular angle bone cutting patient with operation Point, danger area, and demarcate maximum and bone range;
S2, range that the preoperative CT image of mandibular angle bone cutting patient with operation, preoperative photo, prediction postoperative film, maximum are boned, it is defeated Enter osteotomy surface prediction model, predict the amputation line of actual patient, face of boning, in conjunction with AR equipment, real-time rendering visual area amputate line, It bones face, danger area.
The present invention is further arranged to: in step S1, according to the preoperative CT image of mandibular angle bone cutting patient with operation, under crawl Denture rivet point obtains lower denture rivet point reference planes γ;Its inferior alveolar nerve area out of shape and the nervus mentalis area out of shape is marked to be Danger area 1, marks facial artery and posterior facial vein area out of shape is danger area 2;Quantitative evaluation is carried out to each danger area, constructs danger area Data set.
The present invention is further arranged to: to each danger area carry out quantitative evaluation, with parameter indicate each danger area respectively with ginseng Examine the relationship between plane γ, wherein with parameter 35 indicate 1 geometric center of danger area apart from reference planes γ geometric centers away from From indicating the deflection angle in danger area 1 Yu reference planes γ with parameter 36;2 geometric center of danger area distance ginseng is indicated with parameter 37 The distance for examining plane γ geometric center indicates the deflection angle in danger area 2 Yu reference planes γ with parameter 38.
The present invention is further arranged to: according to preoperative CT image, avert danger area, obtains mandibular angle bone cutting patient with operation Maximum is boned range.
The present invention is further arranged to: in step S1, being boned the range amount of progress to the maximum of mandibular angle bone cutting patient with operation Change, including maximum range of boning is split, marks;It is described fractionation be maximum is boned range be split as mandibular amputation line Plane two parts are removed with mandibular osteo-distraction, CT image Direct Mark mandibular amputation line α and mandibular osteo-distraction remove in the preoperative Plane β, while on lower denture, multiple rivet points are marked, and reference planes γ is demarcated according to the rivet point;The mark is Quantitative estimation mandibular amputates line α, mandibular osteo-distraction removal plane the β relationship between reference planes γ respectively.
The present invention is further arranged to: the mark includes: to indicate that mandibular amputates line α geometric center distance with parameter 31 The distance of reference planes γ geometric center;The deflection angle of mandibular amputation line α and reference planes γ is indicated with parameter 32;Use parameter 33 indicate distance of the mandibular osteo-distraction removal plane β geometric center apart from reference planes γ geometric center;It is indicated down with parameter 34 The deflection angle of the removal of jawbone outside plate plane β and reference planes γ.
The present invention is further arranged to: the range input of boning of preoperative CT, preoperative photo, prediction postoperative film, maximum is cut Bone face prediction model predicts amputation line, face of boning.
The present invention is further arranged to: being carried out real-time rendering to the amputation line of different perspectives, face of boning, danger area, is realized Real-time rendering visual area amputates line, face of boning, danger area, and in conjunction with AR system, real-time rendering visual area amputates line, face of boning, danger area, Eyeglass screen is projeced into after visualization of 3 d model is superimposed by AR system with practical visual area.
Compared with prior art, advantageous effects of the invention are as follows:
It bones range, danger area 1. the application according to the preoperative CT of actual patient, obtains maximum, in conjunction with osteotomy surface prediction model, It realizes the prediction for changing range to postoperative facial effect picture, obtains postoperative facial 3D effect maximum change figure, it is ensured that postoperative effect.
2. further, according to the preoperative CT of actual patient, preoperative photo and osteotomy surface prediction model, to actual patient Postoperative effect is predicted, realizes the accurately personalized designs to postoperative effect.
3. further, realizing the real-time rendering of visual area in conjunction with AR equipment, operation precision is improved, operation risk is reduced, Shorten operating time, reduces postoperative complication.
Detailed description of the invention
Fig. 1 is the operation guiding system general construction schematic diagram of a specific embodiment of the invention;
Fig. 2 is the operation guiding system schematic diagram of a specific embodiment of the invention;
Fig. 3 is that the prediction model of a specific embodiment of the invention establishes schematic diagram;
Fig. 4 is the osteotomy surface prediction schematic diagram of a specific embodiment of the invention.
Specific embodiment
Below in conjunction with attached drawing, invention is further described in detail.
Fig. 1 is the scantling plan of this operation guiding system.
Specifically, a kind of operation guiding system of mandibular angle bone cutting art, as shown in Figure 2, comprising the following steps:
S1, according to the related data of the past mandibular angle bone cutting patient with operation, osteotomy surface prediction model study version is established, with newly entering group The related data of mandibular angle bone cutting patient with operation tests osteotomy surface prediction model study version, obtains stable osteotomy surface Prediction model;
Specifically, as shown in figure 3, including the following steps:
A1, the first osteotomy surface parameter is obtained according to the preoperative CT image of the past patient's mandibular angle bone cutting patient with operation, postoperative CT image, In conjunction with preoperative photo, the postoperative film of the past patient, multitask convolutional neural networks are based on, obtain the study of osteotomy surface prediction model Version, obtains operation guiding system 1.0 editions;
A2, the preoperative CT image of new patient in group, postoperative CT image are collected, the second osteotomy surface parameter is obtained, in conjunction with preoperative photo, art Photo afterwards constructs test set, tests osteotomy surface prediction model, stable osteotomy surface prediction model is obtained, in conjunction with both Toward the danger area of patient, the danger area of new patient in group, obtains osteotomy surface prediction model and stablize version, complete operation guiding system 2.0 version.
It is described further below:
The alignment that the preoperative CT image of the past mandibular angle bone cutting patient with operation, postoperative CT image are carried out to pixel scale, is compared Compared with obtained difference is the final osteotomy surface of the past patient, i.e., the first final osteotomy surface tears the first final osteotomy surface open Divide and demarcates.
Firstly, the first final osteotomy surface is divided into the first mandibular amputation line α 1 and the first mandibular osteo-distraction removal plane β 1 Two component parts, directly obtained on CT in the preoperative the first mandibular amputation line α 1 and the first mandibular osteo-distraction remove plane β 1, The markup information of first lower tooth rivet point, the first lower tooth rivet point include multiple points, and multiple lower tooth rivet points determine under first Denture rivet point reference planes γ 1.
Then, quantification treatment is carried out to the first final osteotomy surface, respectively indicates the first mandibular amputation line α 1, the with parameter One mandibular osteo-distraction removes the positional relationship between the lower denture rivet point reference planes γ 1 of plane β 1 and first, that is, under first On the basis of denture rivet point reference planes γ 1, the first mandibular amputation line α 1 is respectively indicated with parameter, the first mandibular osteo-distraction is gone Except the positional relationship of plane β 1, specifically, indicate that the first mandibular amputates 1 the first lower tooth of geometric center distance of line α with parameter 11 The distance of 1 geometric center of column rivet point reference planes γ;The lower denture of the first mandibular amputation line α 1 and first is indicated with parameter 12 The deflection angle of rivet point reference planes γ 1;The first mandibular osteo-distraction removal 1 geometric center distance of plane β the is indicated with parameter 13 The distance of 1 geometric center of denture rivet point reference planes γ once;Indicate that the first mandibular osteo-distraction removes plane β 1 with parameter 14 With the deflection angle of the first lower denture rivet point reference planes γ 1.
Because final osteotomy surface is three-dimensional structure, thus the parameter at same visual angle constitutes a data set, the ginseng of different perspectives Array is at different data sets.
The multiple perspective data collection of multiple perspective data collection, preoperative photo of the preoperative CT of the past patient, the multiple views of postoperative film Angular data collection, final osteotomy surface data set, composing training collection, input multitask convolutional neural networks are trained, and obtain osteotomy Face prediction model learns version, i.e. operation guiding system 1.0 editions.
In this step, learns soft tissue variable to the non-linear effects of final postoperative effect and model, realization is based on The accurate estimation of preoperative CT data, preoperative photo and simulation postoperative effect to osteotomy surface.
Version is learnt for osteotomy surface prediction model, needs to carry out stability test.
Acquisition newly enters the data of group mandibular angle bone cutting art patient, forms test set.
Likewise, the preoperative CT image of new patient in group, postoperative CT image to be carried out to the alignment of pixel scale, compared Compared with obtained difference is the final osteotomy surface of new patient in group, i.e., the second final osteotomy surface.Second final osteotomy surface is carried out It splits and demarcates.
Firstly, the second final osteotomy surface is divided into the second mandibular amputation line α 2 and the second mandibular osteo-distraction removal plane β 2 Two component parts, directly obtained on CT in the preoperative the second mandibular amputation line α 2 and the second mandibular osteo-distraction remove plane β 2, The markup information of second lower tooth rivet point, the second lower tooth rivet point include multiple points, and multiple lower tooth rivet points determine under second Denture rivet point reference planes γ 2.
Then, quantification treatment is carried out to the second final osteotomy surface, respectively indicates the second mandibular amputation line α 2, the with parameter Two mandibular osteo-distractions remove the correlation between the lower denture rivet point reference planes γ 2 of plane β 2 and second, that is, under second On the basis of denture rivet point reference planes γ 2, the second mandibular amputation line α 2 is respectively indicated with parameter, the second mandibular osteo-distraction is gone Except the positional relationship of plane β 2, specifically, indicate that the second mandibular amputates 2 the second lower tooth of geometric center distance of line α with parameter 21 The distance of 2 geometric center of column rivet point reference planes γ;The lower denture of the second mandibular amputation line α 2 and second is indicated with parameter 22 The deflection angle of rivet point reference planes γ 2;The second mandibular osteo-distraction removal 2 geometric center distance of plane β the is indicated with parameter 23 The distance of two lower 2 geometric centers of denture rivet point reference planes γ;Indicate that the second mandibular osteo-distraction removes plane β 2 with parameter 24 With the deflection angle of the second lower denture rivet point reference planes γ 2.
By the data set of the above parameter of different perspectives, the data set of the second final osteotomy surface of new patient in group is constituted.
By the data set of the second final osteotomy surface, preoperative CT, in conjunction with preoperative photo, the postoperative film of new patient in group, structure At test set.
Test set data input osteotomy surface prediction model study version is tested, stable osteotomy surface prediction mould is obtained Type improves the Stability and veracity of operation guiding system.
According to the preoperative CT of the past patient, inferior alveolar nerve area out of shape and the nervus mentalis Qu Wei out of shape of the past patient are marked One danger area 1, marks facial artery and posterior facial vein area out of shape is the first danger area 2;Quantitative evaluation, building are carried out to each danger area First danger area data set.
First danger area is quantified, indicates that denture rivet point reference planes are descended with first respectively in each danger area with parameter Relationship between γ 1 is specifically indicated in 1 the first reference planes of geometric center distance γ of the first danger area, 1 geometry with parameter 15 The distance of the heart indicates the deflection angle in the first danger area 1 and the first reference planes γ 1 with parameter 16;The first danger is indicated with parameter 17 The distance of 2 the first reference planes of geometric center distance γ of danger zone, 1 geometric center, indicates the first danger area 2 and first with parameter 18 The deflection angle of reference planes γ 1.
According to the preoperative CT of new patient in group, marks the inferior alveolar nerve area out of shape of the past patient and nervus mentalis area out of shape is Second danger area 1, marks facial artery and posterior facial vein area out of shape is the second danger area 2;Quantitative evaluation, structure are carried out to each danger area Build the second risk data collection.
Similarly, the second danger area is quantified, indicates that denture rivet point is descended with second respectively in each danger area with parameter Relationship between reference planes γ 2 specifically indicates 1 the first reference planes of geometric center distance of the second danger area with parameter 25 The distance of 2 geometric center of γ indicates the deflection angle in the second danger area 1 and the first reference planes γ 2 with parameter 26;With 27 table of parameter The distance for showing 2 the first reference planes of geometric center distance γ of the second danger area, 2 geometric center, indicates the second danger area with parameter 28 2 and first reference planes γ 2 deflection angle.
The osteotomy surface prediction model for being added to stable by the first danger area data set, the second danger area data set, is cut Bone face prediction model stablizes version, completes building operation guiding system 2.0 editions.
S2, the relevant information of mandibular angle bone cutting art patient is inputted into osteotomy surface prediction model, predicting surgical rear face 3D effect Maximum change range.
To the patient that will carry out mandibular angle bone cutting art, i.e. actual patient, according to its preoperative CT, labeled as its lower tooth socket mind It is third danger area 1 through area out of shape and nervus mentalis area out of shape, marks its facial artery and posterior facial vein area out of shape is third danger area 2;Quantitative evaluation is carried out to each danger area, constructs third danger area data set.
According to the preoperative CT image of mandibular angle bone cutting patient with operation, lower denture rivet point is grabbed, mandibular angle bone cutting art is obtained Patient lower denture rivet point third reference planes γ 3.
According to the preoperative CT image of mandibular angle bone cutting patient with operation, third danger area 1, third danger area 2 are avoided, is obtained down The maximum of jaw angle bone-culting operation patient is boned range.
The maximum of mandibular angle bone cutting patient with operation range of boning is quantified, including maximum range of boning is torn open Divide, mark;Maximum bone range be split as third mandibular amputation line α 3 and third mandibular osteo-distraction remove plane β 3 two Point, CT image Direct Mark third mandibular amputation line α 3 and third mandibular osteo-distraction remove plane β 3 in the preoperative.
Quantitative estimation third mandibular amputate line α 3, third mandibular osteo-distraction removal plane β 3 respectively with third reference planes Relationship between γ 3.Specifically, indicate third mandibular amputation 3 geometric center of line α apart from third reference planes γ with parameter 31 The distance of 3 geometric centers;The deflection angle of third mandibular amputation line α 3 and third reference planes γ 3 is indicated with parameter 32;With ginseng Number 33 indicates distance of third mandibular osteo-distraction removal 3 geometric center of plane β apart from 3 geometric center of third reference planes γ;With Parameter 34 indicates the deflection angle of third mandibular osteo-distraction removal plane β 3 and third reference planes γ 3.
Quantitative evaluation is carried out to each danger area, indicates relationship of each danger area respectively between reference planes γ 3 with parameter, Wherein, distance of 1 geometric center of third danger area apart from 3 geometric center of third reference planes γ is indicated with parameter 35, use parameter 36 indicate the deflection angle in third danger area 1 and reference planes γ 3;2 geometric center distance of third danger area is indicated with parameter 37 The distance of three reference planes γ, 3 geometric center indicates the deflection angle in third danger area 2 Yu third reference planes γ 3 with parameter 38.
Maximum range of boning is not represented as osteotomy surface of finally performing the operation.
By the preoperative CT, preoperative photo, maximum of mandibular angle bone cutting patient with operation bone range input osteotomy surface prediction model Stablize version, obtain postoperative facial maximum change amount 3D effect prediction, is i.e. predicting surgical rear face effect picture changes range.
S3, according to the preoperative CT of mandibular angle bone cutting art patient, amputate line, face of boning, draw and project on eyeglass screen 3-D image see-through, with the fitting of visual area real-time imaging.
Specifically, as shown in figure 4, including the following steps:
B1, the preoperative CT image according to mandibular angle bone cutting patient with operation obtain the lower denture rivet of mandibular angle bone cutting patient with operation Point, danger area, and demarcate maximum and bone range;
B2, range that the preoperative CT image of mandibular angle bone cutting patient with operation, preoperative photo, prediction postoperative film, maximum are boned, it is defeated Enter osteotomy surface prediction model, predict the amputation line of actual patient, face of boning, in conjunction with AR equipment, real-time rendering visual area amputate line, It bones face, danger area.
It is described further below:
According to weight of equipment, performance degree of stability, wearing mode soundness, whether meet the conditions such as the sterile principle of operation, surveys But it tries, select, purchasing suitable wearable augmented reality equipment and its software platform for being used for secondary development, selecting suitable AR (Augmented Reality) equipment, also referred to as wearable augmented reality equipment.
Using augmented reality, the real-time rendering and fitting in osteotomy surface and danger area under visual area are realized, improve angle of mandible The osteotomy precision of bone-culting operation realizes the forewarning function to patient, avoids touching danger zone.
The range input of boning of the preoperative CT of mandibular angle bone cutting patient with operation, preoperative photo, prediction postoperative film, maximum is cut Bone face prediction model stablizes version, predicts the amputation line of actual patient, face of boning;Further according to different perspectives amputation line, bone Face, danger area, in conjunction with AR equipment, real-time rendering visual area amputates line, face of boning, third danger area 1, third danger area 2, will be visual Change after threedimensional model is superimposed by AR system with practical visual area and be projeced into eyeglass screen, completes operation guiding system 3.0 editions.
Specifically, it is based on AR equipment, establishes a set of visualization of 3 d model for osteotomy surface in mandibular angle bone cutting art, and In conjunction with three-dimensional CT image, more of labelling side lower tooth, and multiple rivet points are set accordingly, according to preoperative CT image, label is dangerous Area, and in the three-dimensional mode, determine the spatial relationship of possible rivet point, danger area and osteotomy surface threedimensional model.
During actual operation, the camera carried by the AR equipment that patient dresses shoots visual area and is grabbed Default rivet point is taken, according to the three-dimensional space position relationship built, see-through and art is projected on AR device screen Osteotomy surface, danger area 1,2 image of danger area after the fitting of wild real-time imaging, realize amputated in visual area line, face of boning, danger area 1, The real-time rendering in danger area 2.According to image in a large amount of practical art, filters out and be easy to grab and do not influence spatial relation Construct 3 or so rivet points of stability.Image automatic identification technology based on AR equipment, is constructed in real time to visual area image Analysis identification, automatically grab the system function of default rivet point, and make the system function with build in advance rivet point, danger The 3-dimensional image in area 1, danger area 2 and osteotomy surface combines, and makes patient in actual operation by wearing AR equipment and auxiliary at its Help down, realize the threedimensional model of osteotomy surface project see-throughly on AR device screen, and with from wearer visual angle penetrate AR The function of mandibular portions fitting in the patient visual area that device screen is observed, while being thrown see-throughly on AR device screen Shadow goes out third danger area 1,2 image of third danger area, after corresponding to inferior alveolar nerve and nervus mentalis area out of shape and facial artery and face Vein area out of shape realizes the forewarning function to patient.
Meanwhile during actual operation, operation guiding system is tested and is adjusted, reaches system accurate positioning And projection can be stablized, to realize navigation function of the operation guiding system in mandibular angle bone cutting operation.
S4, function superposition, and continuous testing improvement are constantly carried out to osteotomy surface prediction model, improve operation guiding system.
Operation guiding system 2.0 editions that postoperative facial 3D effect prediction in step S2 is added in step S3, it is perfect Improvement system completes operation guiding system 4.0 editions;
After operation guiding system 4.0 editions debugging repeatedly, it is applied in clinical practice work, need according to the actual situation It wants further progress to upgrade, increases the stability of system, improve the precision in postoperative effect expection and surgical procedure, complete hand Art navigation system 5.0 editions.
For the patient, the application demarcates maximum according to the preoperative CT of actual patient and danger area 1,2 and bones range, passes through It inputs preoperative photo, preoperative CT and maximum and goes bone amount, obtain postoperative facial 3D effect maximum change figure by artificial intelligence technology, Prediction face contour adjustable range realization postoperative to patient is estimated, and the achievable high accurancy and precision to patient's postoperative effect is completed Personalized designs, cost is linked up before desmopyknosis, improves patient satisfaction.
For doctor, the application by label danger area, bone by the maximum that operation guiding system prejudges patient automatically Range, the postoperative prediction face contour adjustable range of backstepping, realize based on 3D photograph and processing system, can be real to postoperative effect It is existing, accurately personalized designs carry out visual area projection to amputation line, face of boning, improve operation precision in conjunction with AR equipment, Danger area is marked under visual area, suggesting effect is played to doctor, reduces operation risk, shortens operating time, reduces postoperative complication.
The embodiment of present embodiment is presently preferred embodiments of the present invention, not limits protection of the invention according to this Range, therefore: the equivalence changes that all structures under this invention, shape, principle are done, should all be covered by protection scope of the present invention it It is interior.

Claims (8)

1. the prediction and real-time rendering method of a kind of mandibular angle bone cutting art, it is characterised in that: the following steps are included:
S1, the preoperative CT image according to mandibular angle bone cutting patient with operation obtain the lower denture rivet of mandibular angle bone cutting patient with operation Point, danger area, and demarcate maximum and bone range;
S2, range that the preoperative CT image of mandibular angle bone cutting patient with operation, preoperative photo, prediction postoperative film, maximum are boned, it is defeated Enter osteotomy surface prediction model, predict the amputation line of actual patient, face of boning, in conjunction with AR equipment, real-time rendering visual area amputate line, It bones face, danger area.
2. prediction according to claim 1 and real-time rendering method, it is characterised in that: in step S1, cut according to angle of mandible The preoperative CT image of osseous surgery patient grabs lower denture rivet point, obtains lower denture rivet point reference planes γ;Mark its lower tooth Slot nerve area out of shape and nervus mentalis area out of shape are danger area 1, mark facial artery and posterior facial vein area out of shape is danger area 2;To each Danger area carries out quantitative evaluation, constructs danger area data set.
3. prediction according to claim 2 and real-time rendering method, it is characterised in that: carry out quantization to each danger area and comment Estimate, indicate relationship of each danger area respectively between reference planes γ with parameter, wherein indicates 1 geometry of danger area with parameter 35 The distance of centre distance reference planes γ geometric center, the deflection angle in danger area 1 Yu reference planes γ is indicated with parameter 36;With ginseng Number 37 indicates distance of 2 geometric center of danger area apart from reference planes γ geometric center, indicates danger area 2 and reference with parameter 38 The deflection angle of plane γ.
4. prediction according to claim 2 and real-time rendering method, it is characterised in that: according to preoperative CT image, avoid endangering Danger zone, the maximum for obtaining mandibular angle bone cutting patient with operation are boned range.
5. prediction according to claim 1 and real-time rendering method, it is characterised in that: in step S1, to mandibular angle bone cutting The maximum of patient with operation range of boning is quantified, including maximum range of boning is split, marked;The fractionation is most Range of boning greatly is split as mandibular amputation line and mandibular osteo-distraction removes plane two parts, in the preoperative under CT image Direct Mark Jawbone amputates line α and mandibular osteo-distraction removes plane β, while on lower denture, marking multiple rivet points, and according to the rivet Point calibration reference planes γ;It is described mark be quantitative estimation mandibular amputation line α, mandibular osteo-distraction removal plane β respectively with ginseng Examine the relationship between plane γ.
6. prediction according to claim 2 and real-time rendering method, it is characterised in that: the mark includes: with parameter 31 Indicate distance of the mandibular amputation line α geometric center apart from reference planes γ geometric center;Indicate that mandibular amputates with parameter 32 The deflection angle of line α and reference planes γ;Indicate mandibular osteo-distraction removal plane β geometric center apart from reference planes γ with parameter 33 The distance of geometric center;The deflection angle of mandibular osteo-distraction removal plane β and reference planes γ is indicated with parameter 34.
7. prediction according to claim 1 and real-time rendering method, it is characterised in that: by preoperative CT, preoperative photo, prediction Postoperative film, maximum bone range input osteotomy surface prediction model, predict amputation line, face of boning.
8. prediction according to claim 7 and real-time rendering method, it is characterised in that: to the amputation line of different perspectives, go Bone face, danger area carry out real-time rendering, and in conjunction with AR system, real-time rendering visual area amputates line, face of boning, danger area, will visualize Threedimensional model is projeced into eyeglass screen after being superimposed by AR system with practical visual area.
CN201910305894.8A 2019-04-16 2019-04-16 A kind of prediction and real-time rendering method of mandibular angle bone cutting art Pending CN109875684A (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201910305894.8A CN109875684A (en) 2019-04-16 2019-04-16 A kind of prediction and real-time rendering method of mandibular angle bone cutting art
CN202010209824.5A CN111227933B (en) 2019-04-16 2020-03-23 Prediction and real-time rendering system for mandibular angle osteotomy

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910305894.8A CN109875684A (en) 2019-04-16 2019-04-16 A kind of prediction and real-time rendering method of mandibular angle bone cutting art

Publications (1)

Publication Number Publication Date
CN109875684A true CN109875684A (en) 2019-06-14

Family

ID=66937688

Family Applications (2)

Application Number Title Priority Date Filing Date
CN201910305894.8A Pending CN109875684A (en) 2019-04-16 2019-04-16 A kind of prediction and real-time rendering method of mandibular angle bone cutting art
CN202010209824.5A Active CN111227933B (en) 2019-04-16 2020-03-23 Prediction and real-time rendering system for mandibular angle osteotomy

Family Applications After (1)

Application Number Title Priority Date Filing Date
CN202010209824.5A Active CN111227933B (en) 2019-04-16 2020-03-23 Prediction and real-time rendering system for mandibular angle osteotomy

Country Status (1)

Country Link
CN (2) CN109875684A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113133802A (en) * 2021-04-20 2021-07-20 四川大学 Bone surgery line automatic positioning method based on machine learning

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009082444A (en) * 2007-09-28 2009-04-23 Lexi:Kk Program for preoperative plan of artificial knee joint replacement operation and operation assisting tool
US20120285002A1 (en) * 2011-05-13 2012-11-15 Lin Ting-Sheng Bone Plate Manufacturing Method
CN104540466A (en) * 2012-05-17 2015-04-22 德普伊新特斯产品有限责任公司 Method of surgical planning
CN106901834A (en) * 2016-12-29 2017-06-30 陕西联邦义齿有限公司 The preoperative planning of minimally invasive cardiac surgery and operation virtual reality simulation method
CN107049475A (en) * 2017-04-19 2017-08-18 纪建松 Liver cancer local ablation method and system
CN109171958A (en) * 2018-10-12 2019-01-11 杭州电子科技大学 The production method of personalized spinal surgery guide plate

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20050042043A (en) * 2001-10-31 2005-05-04 이마그노시스 가부시키가이샤 Medical simulation apparatus and method for controlling 3-dimensional image display in the medical simulation apparatus
CN101396291B (en) * 2007-09-24 2010-12-08 上海交通大学医学院附属第九人民医院 Manufacture method of guide entity of individual mandibular angle hypertrophy operation
US20100305435A1 (en) * 2009-05-27 2010-12-02 Magill John C Bone Marking System and Method
JP5669929B2 (en) * 2010-04-29 2015-02-18 ジンテス ゲゼルシャフト ミット ベシュレンクテル ハフツング Orthognathic implant and method of using the same
CN103106348A (en) * 2013-03-08 2013-05-15 上海交通大学医学院附属第九人民医院 Virtual surgery simulation method and device thereof
WO2015081027A1 (en) * 2013-11-29 2015-06-04 The Johns Hopkins University Patient-specific trackable cutting guides
CN104720877A (en) * 2013-12-18 2015-06-24 王旭东 Application of digitization technology to oral approach mandibular condylar lesion surgical excision
CN105608741A (en) * 2015-12-17 2016-05-25 四川大学 Computer simulation method for predicting soft tissue appearance change after maxillofacial bone plastic surgery
CN108324378A (en) * 2018-02-11 2018-07-27 浙江工业大学 Based on the whole accurate surgery systems of the co-operating craniofacial deformity reduction of major-minor robot and its operation method
CN109061892A (en) * 2018-09-27 2018-12-21 广州狄卡视觉科技有限公司 Plastic surgery medical image Model Reconstruction interacts naked-eye stereoscopic display system and method
CN109464193B (en) * 2018-12-27 2020-12-08 北京爱康宜诚医疗器材有限公司 Data prediction method, device and system

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009082444A (en) * 2007-09-28 2009-04-23 Lexi:Kk Program for preoperative plan of artificial knee joint replacement operation and operation assisting tool
US20120285002A1 (en) * 2011-05-13 2012-11-15 Lin Ting-Sheng Bone Plate Manufacturing Method
CN104540466A (en) * 2012-05-17 2015-04-22 德普伊新特斯产品有限责任公司 Method of surgical planning
CN106901834A (en) * 2016-12-29 2017-06-30 陕西联邦义齿有限公司 The preoperative planning of minimally invasive cardiac surgery and operation virtual reality simulation method
CN107049475A (en) * 2017-04-19 2017-08-18 纪建松 Liver cancer local ablation method and system
CN109171958A (en) * 2018-10-12 2019-01-11 杭州电子科技大学 The production method of personalized spinal surgery guide plate

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113133802A (en) * 2021-04-20 2021-07-20 四川大学 Bone surgery line automatic positioning method based on machine learning

Also Published As

Publication number Publication date
CN111227933A (en) 2020-06-05
CN111227933B (en) 2021-02-19

Similar Documents

Publication Publication Date Title
CN109925055B (en) Full-digital total knee joint replacement surgery robot system and simulated surgery method thereof
Badiali et al. Augmented reality as an aid in maxillofacial surgery: validation of a wearable system allowing maxillary repositioning
RU2714665C2 (en) Guide system for positioning patient for medical imaging
CN109907827A (en) A kind of operation guiding system of mandibular angle bone cutting art
EP3145411B1 (en) Method for 3-d cephalometric analysis
Chapuis et al. A new system for computer-aided preoperative planning and intraoperative navigation during corrective jaw surgery
Huete et al. Past, present, and future of craniofacial superimposition: Literature and international surveys
CN107529968A (en) For observing the device of cavity interior
US10368814B2 (en) Method for cephalometric analysis
CN112043383A (en) Ophthalmic surgery navigation system and electronic equipment
EP3471617B1 (en) Method and system for 3d cephalometric analysis
CN105264459A (en) Haptic augmented and virtual reality system for simulation of surgical procedures
JP2008516727A (en) Digital ophthalmic workstation
CN106806021A (en) A kind of VR surgery simulation systems and method based on human organ 3D models
CN112885436B (en) Dental surgery real-time auxiliary system based on augmented reality three-dimensional imaging
Mamone et al. Monitoring wound healing with contactless measurements and augmented reality
CN106725846A (en) A kind of operation simulation system and method based on human organ 3D models
KR20190108923A (en) Plastic surgery/surgery support system using augmented reality
CN109875683A (en) The method of osteotomy surface prediction model is established in a kind of mandibular angle bone cutting art
Debarba et al. Augmented reality visualization of joint movements for physical examination and rehabilitation
JP2004024739A (en) Method and apparatus for three-dimensional display and coordinate measurement of fundus oculi
WO2022089051A1 (en) Skull correction scheme generation system and construction method therefor, and skull correction scheme acquisition method and apparatus
CN109875684A (en) A kind of prediction and real-time rendering method of mandibular angle bone cutting art
US11406346B2 (en) Surgical position calibration method
CN109620406B (en) Display and registration method for total knee arthroplasty

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20190614