Method and system for analysis of cranial profile image based on neural network and random forest

Abstract

The invention discloses a cranial side image analysis method and system based on neural network and random forest. After the imaging equipment (generally oral and maxillofacial tomography imaging equipment, referred to as CBCT) completes the exposure of the patient's cranial side and image synthesis, the imaging results are input into the anatomical feature marking module of the cranial side, and after a series of computer automatic identification and marking processes, the completed For the marking of important anatomical structures on the image, output the high-precision position of the feature points; then the cranial side report generation module receives the position of each anatomical feature point after manual verification and adjustment by the cranial side anatomical feature marking module, and completes craniofacial medicine The final cranial lateral analysis report is obtained as the basis for the doctor's follow-up diagnosis. The present invention solves the problem of fast and automatic analysis of cranial side images, greatly reduces the physical labor of doctors in the cranial side image analysis process, shortens the diagnosis period, improves the stability of system prediction, and prevents abnormal results from appearing.

Description

technical field [0001] The invention belongs to the technical field of computer-aided diagnosis, and relates to a method and system for automatic analysis of cranial side X-ray images, in particular to an automatic analysis of cranial side X-ray images (hereinafter referred to as cranial side images) based on random forest technology and neural network technology methods and systems. Background technique [0002] X-ray Cranial Imaging (X-ray Cephalometry) technology is an imaging technology that uses X-rays to project radiation on the patient's head to obtain a side perspective view of the patient's head; its functional feature is to use a small radiation dose, Obtain cross-sectional image data of head bones and tissues to provide basis for clinicians' diagnosis. In the lateral imaging results of the brain, there are some characteristic points indicated by the physiological structure, which can provide auxiliary information for the doctor's diagnosis or become the basis for...

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Problems solved by technology

[0006] The technical problem to be solved by the present invention is to provide a cranial side image analysis system based on neural network and random forest, which solves the problems existing in the existing automatic marking technology, solves the problem of fast automatic analysis of cranial side images, and greatly reduces The physical labor of doctors in the process of cranial lateral image analysis shortens the diagnosis cycle

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