We consider in this paper the problem of reconstructing 3D Computed Tomography images from limited data. The problem is modeled as a nonnegatively constrained minimization problem of very large size. In order to obtain an acceptable image in short time, we propose a scaled gradient projection method, accelerated by exploiting a suitable scaling matrix and efficient rules for the choice of the step-length. In particular, we select the step-length either by alternating Barzilai-Borwein rules or by exploiting a limited number of back gradients for approximating second-order information. Numerical results on a 3D Shepp-Logan phantom are presented and discussed.
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Titolo: | A fast gradient projection method for 3D limited data tomography |
Autori: | |
Data di pubblicazione: | Being printed |
Rivista: | |
Handle: | http://hdl.handle.net/11392/2371641 |
Appare nelle tipologie: | 04.1 Contributi in atti di convegno (in Rivista) |