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Article Dans Une Revue Magnetic Resonance Materials in Physics, Biology and Medicine Année : 2015

Gamma regularization based reconstruction for low dose CT

Résumé

Reducing the radiation in computerized tomography is today a major concern in radiology. Low dose computerized tomography (LDCT) offers a sound way to deal with this problem. However, more severe noise in the reconstructed CT images is observed under low dose scan protocols (e.g. lowered tube current or voltage values). In this paper we propose a Gamma regularization based algorithm for LDCT image reconstruction. This solution provides a good balance between the regularizations based on l 0-norm and l 1-norm. We evaluate the proposed approach using the projection data from simulated phantoms and scanned Catphan phantoms. Qualitative and quantitative results show that the Gamma regularization based reconstruction can perform better in both edge-preserving and noise suppression when compared with other regularizations using integer norms.
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Dates et versions

hal-01222764 , version 1 (30-10-2015)

Identifiants

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Junfeng Zhang, Yang Chen, Yining Hu, Limin Luo, Huazhong Shu, et al.. Gamma regularization based reconstruction for low dose CT. Magnetic Resonance Materials in Physics, Biology and Medicine, 2015, 60 (17), pp.6901-6921. ⟨10.1088/0031-9155/60/17/6901⟩. ⟨hal-01222764⟩
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