Enhancement of Lesions in CT Images of Lung Cancer Based on MIMICS Software

Abstract

In order to explore the three-dimensional reconstruction of lung cancer CT images by MIMICS software, the purpose of enhancing the effect of the lesion area is realized, and the visualization model can be realized, which can effectively assist the early diagnosis of lung cancer and the surgical treatment of lung cancer. Using lung CT scan data from lung cancer patients, semi-automated segmentation methods are used to segment the lung tumors in MIMICS software to create an individualized lung cancer model. MIMICS software accurately and efficiently distributes the model according to the gray values of different tissues, and successfully establishes a human body chest finite element model with realistic shape and accurate structure. The model includes chest skin, bones, lungs, pulmonary arteries, pulmonary veins, and tracheobronchial trees, providing precise model support for finite element analysis. This study successfully constructs a three-dimensional digital model of individualized lung cancer. The model has high geometric similarity and strong stereoscopic effect. It truly reflects the morphological characteristics of lung cancer and the spatial relationship between adjacent structures, which makes the imaging effect of lung cancer lesions more prominent. By moving, separating, combining, and revealing the model, multi-angle observation and measurement can be performed, which facilitates preoperative planning and shortens the operation time.