A study on regularization parameter choice for interior tomography based on truncated Hilbert transform

Junfeng Wu; Xuanqin Mou; Shaojie Tang

doi:10.1117/12.877609

16 March 2011 A study on regularization parameter choice for interior tomography based on truncated Hilbert transform

Junfeng Wu, Xuanqin Mou, Shaojie Tang

Proceedings Volume 7961, Medical Imaging 2011: Physics of Medical Imaging; 79612Z (2011) https://doi.org/10.1117/12.877609
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

For interior tomography based on truncated Hilbert transform (THT), the recently proposed truncated singular value decomposition (TSVD) reconstruction method uses a regularization parameter given directly. In this paper, a method of choosing the regularization parameter is presented based on L-curve to get an optimal regularization parameter in theoretical sense. Furthermore, we develop a Tikhonov regularization method in comparison to TSVD. Simulation results indicate that both of the two regularization methods with the optimal regularization parameters have good performances on the image quality for both cases of noise-free and noisy projections.

Citation Download Citation

Junfeng Wu, Xuanqin Mou, and Shaojie Tang "A study on regularization parameter choice for interior tomography based on truncated Hilbert transform", Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging, 79612Z (16 March 2011); https://doi.org/10.1117/12.877609

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