Research on Fusion Method of Functional Image and Anatomical Image Based on Anatomical Knowledge Model

Abstract

Medical imaging is one of the important sources of clinical diagnostic information. According to the information connotation provided by medical images, medical images can be divided into two categories: anatomical structure images (CT, MRI, B-ultrasound, etc.) and functional images (SPECT, PET, etc.). The development of medical imaging technology and the practice of clinical application tell us that there is no single way to solve the complex clinical problems, and each imaging technology has its own advantages and disadvantages, including its own. In order to improve the automation and reliability of medical image fusion, this paper proposes a fully automatic medical CT image fusion method based on knowledge model. This method provides a general model for medical image fusion. This method improves the automation and reliability of medical image fusion. Because of its extensibility, this method provides a general model for medical image processing based on knowledge.