Analysis of Segmentation and Modeling of Lung Cancer Images Scanned Continuously by Computed Tomography Based on Materiaise's Interactive Medical Image Control System

The purpose of this study is to explore the value of CT (computed tomography) continuous scanning by MIMICS (Materiaise's interactive medical image control system) in segmentation modeling of lung cancer images and to analyze the process of building a three-dimensional finite element model of lung cancer quickly and accurately. In this study, MIMICS software is used to conduct data collection of routine CT continuous image for 12 patients diagnosed with lung cancer, and a database is established. The image is divided according to a specific rule, such as grayscale, space, texture, geometric shape and other characteristics, to form a series of meaningful regions. Software MIMICS17.0 is used to perform visualization segmentation, extraction, and 3d rendering to images, followed by data transformation. Because the 3d images constructed by MIMICS software have the advantages of strong editability and wide subsequent application, the lung cancer model images constructed in this study are lifelike in shape, with high geometric similarity and strong sense of solidity, truly reflecting the morphological characteristics of lung cancer and the spatial relationship between adjacent structures. Therefore, by transparently treating the lungs, the internal tumor, bronchial system and vascular system can be observed directly, thereby better presenting the spatial location of the lung tumor. However, due to the limitations of the software itself, the XYZ data of lung of space-occupying lesions could not be output by the program, which needs to be further studied and verified.