Segmentation Methods On Kidney CT Sequence Images

3D kidney segmentation in the CT scan volumes technique is used for the treatment of patients by application of a group of CT images photographed by medical CT imaging apparatus for rapid segmentation to target the kidney area. The 3D reconstruction technology, as a key image data processing technology plays an important role in three-dimensional medical images of organs and tissues’ visualization, virtual surgery, biological system simulation, etc. With the continuous development of modern medical imaging technology, and equipment, the needs for a large number of medical image data processing are increasing. The existing medical image processing technology is more concerned about the extraction of single medical image information, but it’s seldom to see taking the image sequence division process as a whole. This study proposes a approach for the fast segmentation method for CT image sequences kidneys, which will be discussed through relevant research questions as following.1. Single image segmentation requires less manual intervention to complete the high-precision segmentation.For single medical image segmentation to the specified destination, traditional practices are totally dependent on artificial extraction, which ensures accuracy requirements of segmentation to some extent, but this is time-consuming and labor-intensive, but powerless to fast condition in clinical analysis.However, the reliability of fully automated segmentation method at this stage cannot be guaranteed, semi-automatic segmentation technique by some manual intervention are to be the choice. Meanwhile, in order to ensure efficiency, not too frequent human intervention is required.2. The sequence of image processing mechanism associates fast.There is some continuity between the image sequences that are interconnected. In order to accelerate the speed and automation of the process, it’s quite important for how to use the correlation between the images. This paper presents a sequence of image processing based on target tracking mechanism in dealing with continuous images, to complete the next task image segmentation without additional user input.3. The practical processing tools. The ultimate goal of this project is to develop a practical clinical tool in medical image processing. Apart from the fast segmentation and reconstruction mentioned in achieving this task, some generic processing operations are requested to be added as we should take the user’s needs into account.Besides, taken the scalability of the tool into consideration, we need to leave an interface in the process of building tool.This paper focuses on CT image sequences for kidney treatment, at the conclusion of the prior art, based on the completion of the design and implementation of segmentation methods. On this basis, it can be carried out to improve the existing medical image segmentation by further research.