Medical imaging, image/shape processing and analysis has been a rather popular research area in the past decade, not only because of the great importance of the problems, but also their difficulties. Numerous researchers with expertise ranging from radiology and neurology to computer science, engineering and mathematics are working extensively in this area. In my talk, I will first discuss a tight wavelet frame based cone beam CT reconstruction model, which falls into the category of tomographic imaging. The model is motivated by the recent bloom of research on frame based image. Then I will introduce a frame based segmentation model for general medical image segmentation problems. This model is motivated by the ideas of the total variation based segmentation models (convexified Chan-Vese Model). After that, I will move to the topic on biological shape processing and analysis. Within this category, I will mainly discuss the following two topics: brain aneurysm segmentation in 3D biomedical images and multiscale representation for shapes and its applications in blood vessel recovery (surface inpainting) and others. Some future work and ongoing projects will be mentioned in the end.