Prediction and real-time rendering system for mandibular angle osteotomy

Abstract

The invention discloses a prediction and real-time rendering system for mandibular angle osteotomy, which comprises a calibration subsystem, a prediction subsystem and a rendering subsystem, and is characterized in that the calibration subsystem is used for obtaining a lower dentition rivet point and a danger area of a mandibular angle osteotomy patient according to a preoperative CT image of themandibular angle osteotomy patient and calibrating a maximum osteotomy range; wherein the prediction subsystem is used for inputting a preoperative CT image, a preoperative photo, a prediction postoperative photo and a maximum osteotomy range of a mandibular angle osteotomy patient, into an osteotomy surface prediction model and predicting an actual patient's cutting line and an osteotomy surface,and the rendering subsystem is used for rendering the surgical field cutting line, the osteotomy surface and a danger area in real time in combination with AR equipment. According to the pre-operation CT, the pre-operation picture and the osteotomy surface prediction model of the actual patient, the operation field of the actual patient is rendered in real time, the operation precision is improved, the operation risk is reduced, the operation time is shortened, and operation complications are reduced.

Description

Technical field [0001] The invention relates to the technical field of mandibular angle osteotomy, in particular to a prediction and real-time rendering system for mandibular angle osteotomy. Background technique [0002] Due to the changes in the facial appearance of patients after mandibular angle osteotomy, in addition to the amount of mandibular osteotomy, it is also partly related to changes in soft tissue volume caused by changes in local soft tissue tension. Therefore, the amount of bone removal for mandibular angle osteotomy is not a subtraction between the patient’s facial appearance before the operation and the predicted effect after the operation. In the past, the 3D design of the operation effect was performed solely by means of 3D CT and 3D facial scanning camera system, which was not accurate. To predict the amount of bone removal and the position of the osteotomy surface during the mandibular angle osteotomy to achieve the postoperative prediction effect. [0003] T...

AI Technical Summary

Problems solved by technology

However, there are currently three deficiencies in this system: (1) Additional fixed landmarks are required: the osteotomy line is determined by instructing the patient to wear a dental brace with a marking module. There is a high risk of relative displacement between the module and the mandible, which leads to errors in the judgment of the osteotomy line and reduces the safety of the operation; The stability of the relative positional relationship between the marking module and the mandibular body, but because the actual operation space of the mandibular angle osteotomy through the intraoral approach is narrow and deep, the operation of fixing the marking module itself is difficult, and the marking module is too large relative to the surgical field. Large, applicable cases that can achieve proper placement of the marker module are extremely limited

(2) The surgical navigation system adopts the mode of mechanical discontinuous drilling for osteotomy. Since the hole through the bone tissue formed by drilling is linear, this mode is suitable for mandibular outer plate removal at the same time. It is not applicable to some cases, and the osteotomy surface formed is a plane rather than a curved surface, which limits the application range of the surgical navigation system to a large extent

(3) The surgical navigation system does not take into account the soft tissue changes after mandibular angle osteotomy, and the design of the osteotomy line is entirely based on the operator's previous experience without quantitative indicators. Although the system improves the safety of surgery , but it has no advantages in accurately predicting the postoperative effect of patients and improving patient satisfaction

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