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A Variational Reconstruction Method for Undersampled Dynamic X-ray Tomography based on Physical Motion Models. (arXiv:1705.06079v1 [math.NA])
来源于:arXiv
In this paper we study the reconstruction of moving object densities from
undersampled dynamic X-ray tomography in two dimensions. A particular
motivation of this study is to use realistic measurement protocols for
practical applications, i.e. we do not assume to have a full Radon transform in
each time step, but only projections in few angular directions. This
restriction enforces a space-time reconstruction, which we perform by
incorporating physical motion models and regularization of motion vectors in a
variational framework. The methodology of optical flow, which is one of the
most common methods to estimate motion between two images, is utilized to
formulate a joint variational model for reconstruction and motion estimation.
We provide a basic mathematical analysis of the forward model and the
variational model for the image reconstruction. Moreover, we discuss the
efficient numerical minimization based on alternating minimizations between
images and motion vectors. A variety of 查看全文>>