Tomographic CT image processing and tumor identification

As a great threat to human health, tumors have the characteristics of low cure rate and high recurrence rate. The survival rate and cure effect of tumors largely depend on the timely detection of tumors. Timely tumor diagnosis and screening can greatly improve the cure rate of patients. At this stage, early tumor screening mainly relies on CT scans, and the diagnostic results of CT scans rely on doctors’ experience in diagnosis. In order to assist doctors in diagnostic decision-making and improve the accuracy of diagnosis, this article designs a method for processing and screening of CT image. This method performs denoising preprocessing, binary segmentation, connected area selection, mathematical morphological repair, and others on the scanned CT images sequentially. To obtain the accurate area to be processed on the CT image, and then extracts the substantial tissue area through the interactive seed point growth method. This article performed the above processing on 20 brain cross-sectional CT images to achieve the extraction of brain parenchymal tissue areas. For intuitive display in practical applications, this article performed a three-dimensional reconstruction of the brain cross-sectional CT images to achieve the extraction of brain parenchymal tissue. Interactive, visual observation, and three-dimensional refinement processing were used to initially screen out the tumor areas in the brain tissue.