Object-based reconstruction using coupled tomographic flows
We develop a new geometric curve evolution approach to tomographic reconstruction problems including multiple objects having different levels of intensity, and background with varying intensity. We use two contours to represent the boundaries of distinct object regions with different intensity levels and a set of basis functions and expansion coefficients to describe the background. By designing coupled "tomographic flows", the problem of estimating the two contours and intensity coefficients is recast into a curve evolution problem. A new "repelling" force between the two coupled curves is proposed for the reconstruction algorithms to accelerate convergence. The performance of the coupled curve evolution method is demonstrated via a Radon inversion example. The results show that our curve evolution method achieves improved shape reconstruction over comparable regularization techniques.