Résumé
Image guided surgical navigation system is the most advanced surgical apparatus, which develops most rapidly and has great application prospects in neurosurgery, orthopaedics, E.N.T. department etc. In current surgical navigation systems, windowing, segmenting and registration of medical images all depend on manual operation, and automation of image processing is urgently needed. This paper proposes the algorithm which realizes very well automatic windowing and segmentation of medical images: first, we analyze a lot of MRI and CT images and propose corresponding windowing algorithm according to their common features of intensity distribution. Experiments show that the effects of windowing of most MRI and CT images are optimized. Second, we propose the seed growing algorithm based on intensity connectivity,which can segment tumor and its boundary exactly by simply clicking the mouse, and control dynamically the results in real time. If computer memory permits, the algorithm can segment 3D images directly. Tests show that this function is able to shorten the time of surgical planning, lower the complexity, and improve the efficiency in navigation surgery.