| Medical imaging is an innovative discovery in the field of medical diagnostics,Medical image processing technology is more and more important in the field of medical research and clinical medicine.Because of the three-dimensional reconstruction and medical image processing,doctors do not have to do an anatomical surgery and can observe and diagnose the lesion area in a multi-angle,multi-form.This revolutionary new technology changes the traditional medical diagnostic mode.It improves not only the diagnostic efficiency but also the accuracy.In this paper,we introduce the whole process of medical image analysis and processing which starts from the two-dimensional abdominal medical image to the three-dimensional reconstruction of the organ.Medical images are different from common images.They need to be format conversion and displayed clearly and accurately on personal computers.Format conversion is the basis of other medical imaging studies.A typical medical image is very complex,may contain many organs and tissues,Sue to the impact such as imaging equipment and human factors often have more or less interference information in the imaging process,medical image preprocessing process seems insignificant but can play a supporting role for the quality and usability of other algorithms.According to the imaging principle and imaging characteristics of various medical images,it may not all the information is helpful for medical diagnosis.It is very important to split the interested tissues and organs in the medical image,and it have a very positive impact on clinical research and development.In addition,three-dimensional reconstruction of organs and tissues based on two-dimensional slice sequence is very useful in the field of medical image analysis.It can reconstruct the three-dimensional models of various organs,which can be helpful for tissue disease prediction and internal structure exploration.Not only can improve the diagnostic accuracy,but also provide doctors and related scholars a full range of three-dimensional visual organ model.This paper first introduces the DICOM standard from the purpose of research,then converts the medical image into a bitmap image,and displays the bitmap with the device independent display mode.Depending on the importance of the information,it is important to read important information related to the patient,device,and image parameters in the DICOM header.In this paper,the preprocessing method is briefly introduced,including the gray scale transformation and image enhancement,as well as the commonly used geometric transformation methods including translation.The image enhancement is divided into smooth,sharpening operations.Comparison of traditional medical image segmentation methods,we propose an automated segmentation of multiple organs in medical image data in the paper.The purpose of our research is to build superpixels and use them to predict more accurate segmentation.The superpixel segmentation method adapts to various imaging conditions in CT images and effectively incorporates the interrelationships among multiple organs.The framework of this method is as follows:(1)Clustering super pixels according to pixel correlation and position proximity(2)Introducing the distribution structure of organ spatial structure and modifying the segmentation process of multiple organs.In our framework,we use conventional single-organ segmentation methods to segment the predict the organ,the use super-pixel clustering to split the remaining organs.Then we do a further study of the segmentation results,the Marching Cubes(MC)method is studied on the basis of the segmentation of interest in two-dimensional slices.For the standard MC algorithm,the key points and difficulties of the algorithm are analyzed from the contours of the isosurface,the intersection point of the isosurface and the voxel boundary and the calculation of the isosurface normal vector.Finally,the reconstructed 3D model is given for the specific organ. |
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