3D Visualization Diagnosis Method Of Breast Cancer Based On Mechanical Imaging

Breast cancer is one of the most common malignant tumor of women all over the world. In recent years, the incidence of breast cancer increased dramatically and had a tendency to young people, which was a serious threat to female's life and health. Related studies had shown that most patients had been found for locally advanced cancer, as breast cancer had a slow growth cycle and no obvious symptoms, so early diagnosis and treatment is of great significance for the prevention and treatment of breast cancer. At present the method of clinical diagnosis of breast cancer has clinical palpation, ultrasonic, X-ray and MRI, each have advantages and disadvantages of the application and accuracy.For early diagnosis of breast, a new method is proposed based on mechanical imaging. Mechanical imaging is a kind of new medical visualization diagnostic technique, it uses pressure sensor array instead of human finger, by measuring the counter-acting force of different tissues to reconstruct the 3D elastic distribution of human tissue, and moreover this method can acquire the size, shape and hardness of breast lump. The following is the main research content of this paper:(1) The purpose of study is presented. A large number of references are collected and referred to, leading to an overview of the current national and international situation and developmental trends in the field of clinical diagnosis of breast cancer.(2) The principle of mechanical imaging of soft tissue is analyzed, discuss the influence of different parameters on the stress distribution by using the method of finite element analysis, and study the source of noise of mechanical imaging.(3) For the pressure array, which is independent research and development, this paper establishes a set of image processing algorithm, analyzes each step of the image processing method and key technology, using least squares surface fitting, image segment and image stitching to reduce the elastic noise and improve the quality of the image.(4) Effective breast tumor mobility detection method is proposed, and realize the three-dimensional elasticity reconstruction of soft tissue by using pressure distribution under different pressure.(5) A neural network model has been set up for the diagnosis of breast cancer, the neural network is trained by finite element analysis, which can realize the measurement of the breast size, hardness and depth.The experimental results demonstrated the method of breast cancer diagnosis in this paper, can effectively filter out elastic noise, realize three-dimensional visualization and diagnosis of breast cancer and meet the design requirement.