Design And Implementation Of Visualization Software For 3D Model Of Breast Based On

In recent years, the majority of women of a certain age the incidence rate of breast cancer increases every year by frequent media, especially the younger age of onset as a whole tends to news triggered a large majority of women’s inner fear and anxiety, it also means the timely detection and treatment of breast disease for human life and health increasingly has great significance. Meanwhile, according to many magazines and media reports indicate that, with the changing environment of human life, the impact on the incidence of female breast cancer will exceed influenced by genetic factors, so experts predict the incidence of breast cancer in women in urban and rural areas will further rise, while large number of our population, so for accurate and convenient detection of breast disease will have a huge significance.In this paper, mature computer visualization techniques, statistical modeling techniques to develop a three-dimensional model of breast cancer visualization system, which include: image preprocessing, breast interested in organ segmentation and contour extraction point cloud data simplification and optimization, three-dimensional model reconstruction and interactive features such as three-dimensional model. Meanwhile, the system can not only split the breast to any organ and contour extraction, can be accurately reconstructed to allow doctors to observe lung lesion visualization, thus effectively improve the success rate of treatment, which is a very important life and health of women significance. The system not only can accurately split mammary organ of interest, but also accurate segmentation of the lung parenchyma, liver, colon and other organs of the lesions, these doctors closer to the suspected diagnosis of lesions, greatly reducing the number of film-reading doctor to improve diagnostic efficiency while also overcoming the misdiagnosis and missed diagnosis due to the human eye and the human eye to eye fatigue insensitive gray value generated, effectively improve the efficiency and accuracy of breast cancer detection to help doctors make good decisions.