A multi-information 3D medical image high-precision registration method

Abstract

The invention discloses a multi-information 3D medical image high-precision registration method. The method comprises the following steps: respectively extracting outer contour point clouds of a reference image and a floating image; respectively calculating the centroids of the reference image and the floating image; respectively translating the centroids of the two modes to coincide with the original point to obtain a new reference mode and a new floating mode; Respectively calculating to obtain a first characteristic axial vector and a second characteristic axial vector of the reference modeand the floating mode; constructing a rotation operator according to the obtained characteristic axial quantity, and completing rotation of the floating image; and completing registration after translation and rotation. The method is simple and intuitive in geometrical significance, high in registration precision and universality through experiment and objective reference comparison and analysis,and convenient for doctors to accurately analyze the illness state of a patient.

Description

[0001] This application is a divisional application with application number: 201610650011.3, application date: 2016.08.09, and name "multi-information 3D medical image registration method based on extracranial contour feature geometric invariance". technical field [0002] The invention relates to a multi-information 3D medical image registration method based on geometric invariants of extracranial contour features. Background technique [0003] In the process of diagnosis, treatment and operation of patients, doctors often collect images of the internal tissue structure of the human body in a non-invasive way. Through corresponding imaging technology, different aspects of the status information of the same part of the patient's body can be observed through corresponding medical images. arrive. A single type of medical image cannot provide comprehensive and rich disease information, but different medical image information provides multiple references for doctors to comprehen...

AI Technical Summary

Problems solved by technology

In the past, doctors could only make judgments on multiple single independent images based on experience, and fuse these three-dimensional rigid body images or deformation information in their minds.

This method is a great test for the accuracy of the doctor's experience, and it varies from person to person. Inaccurate judgment may cause unpredictable risks to the diagnosis result.