Improving Low-dose Cardiac CT Images based on 3D Sparse Representation - Université de Rennes Access content directly
Journal Articles Scientific Reports Year : 2016

Improving Low-dose Cardiac CT Images based on 3D Sparse Representation

Abstract

Cardiac computed tomography (CCT) is a reliable and accurate tool for diagnosis of coronary artery diseases and is also frequently used in surgery guidance. Low-dose scans should be considered in order to alleviate the harm to patients caused by X-ray radiation. However, low dose CT (LDCT) images tend to be degraded by quantum noise and streak artifacts. In order to improve the cardiac LDCT image quality, a 3D sparse representation-based processing (3D SR) is proposed by exploiting the sparsity and regularity of 3D anatomical features in CCT. The proposed method was evaluated by a clinical study of 14 patients. The performance of the proposed method was compared to the 2D spares representation-based processing (2D SR) and the state-of-the-art noise reduction algorithm BM4D. The visual assessment, quantitative assessment and qualitative assessment results show that the proposed approach can lead to effective noise/artifact suppression and detail preservation. Compared to the other two tested methods, 3D SR method can obtain results with image quality most close to the reference standard dose CT (SDCT) images

Domains

Bioengineering

Dates and versions

hal-01301540 , version 1 (12-04-2016)

Identifiers

Cite

Luyao Shi, Yining Hu, Yang Chen, Xindao Yin, Huazhong Shu, et al.. Improving Low-dose Cardiac CT Images based on 3D Sparse Representation. Scientific Reports, 2016, 6 (1), pp.22804. ⟨10.1038/srep22804⟩. ⟨hal-01301540⟩
53 View
0 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More