A level set method for Bayesian tomographic reconstruction
Proceedings IEEE International Symposium on Biomedical Imaging - Trang 665-668
Tóm tắt
We present a level-set method for Bayesian tomographic reconstruction. A novel image prior is derived from the mean curvature evolution of level sets of an image. As it has been studied in image processing with nonlinear diffusion, this prior encourages the stabilization of an edge while the reconstructed image is smoothed along both sides of the edge. An algorithm of iterated coordinate decent was implemented with the proposed prior using Brent's method for one-dimensional optimization. Our simulation results demonstrated that our algorithm can outperform existing priors for preserving edges during tomographic reconstruction without introducing additional artifacts.
Từ khóa
#Level set #Bayesian methods #Tomography #Image reconstruction #Kinetic energy #Image processing #Optimization methods #Image restoration #Mathematics #Computer scienceTài liệu tham khảo
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