Research On Image Guided Computer-Assisted Intervention Surgery Navigation

Image guided intervention surgery navigation is a minimally invasive cancer ther-apy which utilizes multi-model medical image for intra-operative surgery guidance, andit is a cross-discipline research topic involving artificial intelligence, medical image pro-cessing, real-time three-dimensional graphics and its application to surgery could signifi-cantly improve surgical result and reduce surgery trauma. This thesis focus on thoracoab-dominal intervention surgery planning and nagivation, with application to percutaneousmicrowave ablation, and the major work and contributes include:(1) A novel graph cat based 3D medical image segmentation algorithm is proposed.The algorithm is based on computer unified device architecture and provided a methodfor the construction of graph data structure of massive 3D medical image data. The en-ergy function for region and boundary is designed for the optimization problem, and theodd-even operation style is introduced to solve the thread con?ict problems in parallelcomputing. Experiments show that this method is well suited for live and lung seg-mentation and the performance of segmentation is significantly improved compared totraditional methods.(2) A novel preoperative surgery planning method for percutaneous microwave ab-lation is proposed. An iterative framework for necrosis field simulation and 3D necrosiszone reconstruction is introduced here, and the necrosis model is further superimposedto patient anatomy structures. Experiments have been performed on patient with hepaticand lung cancer and the results show that this method is accurate for surgery plan andcould be used as an assistant to the clinical practice.(3) An integrated solution for thoracic cavity and abdominal intervention surgerynavigation is proposed. Human body pose immobilization and dynamic monitoring ofrespiratory status is utilized to reduce the navigation error, and realtime CT/US imagefusion is used to feedback the accurate needle insertion position. Experiments shows thatthe clinical precision of navigation could be improved by this method.(4) A GPU based real-time volume rendering method is proposed and implementedto accelerate the rendering speed. Massive medical image volume data is visualized inhigh performance GPU algorithm, and local illumination computation is implemented forhigh quality rendering. The volume rendering method could well fit the requirement for real-time visualization in surgery planning and navigation.(5) An intervention surgery planning navigation system is designed and imple-mented for thoracic cavity and abdominal surgery. Experiments shows that this sys-tem could achieve good results in clinical trials through comparison of preoperative andpostoperative CT images. The development of this technique represented a significantadvance from the traditional ways for cancer therapy and significantly extends the indi-cations of minimally invasive cancer therapy technology.