Bilateral Weighted Relative Total Variation for Low-Dose CT Reconstruction.

Low-dose computed tomography (LDCT) has been widely used for various clinic applications to reduce the X-ray dose absorbed by patients. However, LDCT is usually degraded by severe noise over the image space. The image quality of LDCT has attracted aroused attentions of scholars. In this study, we pr...

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Publicado en:Journal of Digital Imaging Vol. 36; no. 2; pp. 458 - 468
Autores principales: He, Yuanwei, Zeng, Li, Chen, Wei, Gong, Changcheng, Shen, Zhaoqiang
Formato: diagnostic images equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Apr2023
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2023
      vid: 36
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      pub: Springer Nature
      place: New York, New York
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        atl: Bilateral Weighted Relative Total Variation for Low-Dose CT Reconstruction.
      aug:
        au:
          He, Yuanwei
          Zeng, Li
          Chen, Wei
          Gong, Changcheng
          Shen, Zhaoqiang
        affil: College of Mathematics and Statistics, Chongqing University, 401331, Chongqing, China
      sug:
        subj:
          Tomography, X-Ray Computed Methods
          Image Processing, Computer Assisted
          Dose-Response Relationship, Radiation
          Head Radiography
          Human
          X-Rays
          Radiographic Image Interpretation, Computer-Assisted
          Experimental Studies
          Algorithms
          Funding Source
      ab: Low-dose computed tomography (LDCT) has been widely used for various clinic applications to reduce the X-ray dose absorbed by patients. However, LDCT is usually degraded by severe noise over the image space. The image quality of LDCT has attracted aroused attentions of scholars. In this study, we propose the bilateral weighted relative total variation (BRTV) used for image restoration to simultaneously maintain edges and further reduce noise, then propose the BRTV-regularized projections onto convex sets (POCS-BRTV) model for LDCT reconstruction. Referring to the spacial closeness and the similarity of gray value between two pixels in a local rectangle, POCS-BRTV can adaptively extract sharp edges and minor details during the iterative reconstruction process. Evaluation indexes and visual effects are used to measure the performances among different algorithms. Experimental results indicate that the proposed POCS-BRTV model can achieve superior image quality than the compared algorithms in terms of the structure and texture preservation.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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