Periodontal disease CBCT longitudinal data recording and analyzing method

Abstract

The invention discloses a periodontal disease CBCT longitudinal data recording and analyzing method. A cone beam CT machine is used for obtaining three-dimensional volume data of an oral cavity patient, data three-dimensional space correction is carried out, because CBCT data shooting angles are different, shooting machines are different, and imaging results are different; normalizing is carried out on the image processed in the second step or correction is carried out on a gray value of the image; disease prediction is carried out on new patient information, and then a corresponding image report can be written manually or automatically. According to the scheme, data acquisition at different moments is carried out; the three-dimensional space correcting is carried out on the same tissue ofthe data at different moments in the same coordinate system; a common anatomical mark point or mark position is determined for accurate registration, gray value normalization, and image region segmentation is realized (region-of-interest segmentation), progress factors of periodontal diseases are analyzed in combination with clinical electronic medical record information, information difference between longitudinal time series data is analyzed, and a suggested diagnosis and treatment scheme is provided.

Description

technical field [0001] The invention relates to the technical field of medical analysis, in particular to a method for recording and analyzing longitudinal data of periodontal disease CBCT. Background technique [0002] Due to the particularity of human tissue structure, general image processing methods cannot be directly applied. In recent years, the image segmentation problem has been a popular research object in the field of biomedical engineering, and it is also a basic problem in the application of 3D printing technology in the medical field. There are also different methods for the segmentation of different tissues and organs of the human body. In the process of tooth segmentation, there are some complicated problems, such as: at different times, the shooting parameters of the same patient are different; the densities of mandibular teeth and periodontal ligament are similar, and it is difficult to distinguish; the same tooth is at different positions of the crown and ...

AI Technical Summary

Problems solved by technology

In the process of tooth segmentation, there are some complicated problems, such as: at different times, the shooting parameters of the same patient are different; the densities of mandibular teeth and periodontal ligament are similar, and it is difficult to distinguish; the same tooth is at different positions of the crown and root, The bone density is slightly different, and the gray value in CBCT imaging is different; at the molar position, it is more difficult to segment multiple teeth; the gap between adjacent teeth is small, and the tooth outline is not clear in CBCT imaging, etc.

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