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A CT Reconstruction Algorithm Based on L1/2 Regularization.
Chen, Mianyi; Mi, Deling; He, Peng; Deng, Luzhen; Wei, Biao.
Afiliación
  • Chen M; The Key Lab of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044, China.
  • Mi D; The Key Lab of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044, China.
  • He P; The Key Lab of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044, China.
  • Deng L; The Key Lab of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044, China.
  • Wei B; The Key Lab of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044, China.
Comput Math Methods Med ; 2014: 862910, 2014.
Article en En | MEDLINE | ID: mdl-24834109
Computed tomography (CT) reconstruction with low radiation dose is a significant research point in current medical CT field. Compressed sensing has shown great potential reconstruct high-quality CT images from few-view or sparse-view data. In this paper, we use the sparser L1/2 regularization operator to replace the traditional L1 regularization and combine the Split Bregman method to reconstruct CT images, which has good unbiasedness and can accelerate iterative convergence. In the reconstruction experiments with simulation and real projection data, we analyze the quality of reconstructed images using different reconstruction methods in different projection angles and iteration numbers. Compared with algebraic reconstruction technique (ART) and total variance (TV) based approaches, the proposed reconstruction algorithm can not only get better images with higher quality from few-view data but also need less iteration numbers.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Interpretación de Imagen Radiográfica Asistida por Computador / Tomografía Computarizada por Rayos X Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Math Methods Med Asunto de la revista: INFORMATICA MEDICA Año: 2014 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Interpretación de Imagen Radiográfica Asistida por Computador / Tomografía Computarizada por Rayos X Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Math Methods Med Asunto de la revista: INFORMATICA MEDICA Año: 2014 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos