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A CT reconstruction algorithm based on non-aliasing Contourlet transform and compressive sensing.
Deng, Lu-zhen; Feng, Peng; Chen, Mian-yi; He, Peng; Vo, Quang-sang; Wei, Biao.
Afiliación
  • Deng LZ; The Key Lab of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044, China.
  • Feng P; The Key Lab of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing 400044, China.
  • Chen MY; 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.
  • Vo QS; 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: 753615, 2014.
Article en En | MEDLINE | ID: mdl-25101142
Compressive sensing (CS) theory has great potential for reconstructing CT images from sparse-views projection data. Currently, total variation (TV-) based CT reconstruction method is a hot research point in medical CT field, which uses the gradient operator as the sparse representation approach during the iteration process. However, the images reconstructed by this method often suffer the smoothing problem; to improve the quality of reconstructed images, this paper proposed a hybrid reconstruction method combining TV and non-aliasing Contourlet transform (NACT) and using the Split-Bregman method to solve the optimization problem. Finally, the simulation results show that the proposed algorithm can reconstruct high-quality CT images from few-views projection using less iteration numbers, which is more effective in suppressing noise and artefacts than algebraic reconstruction technique (ART) and TV-based reconstruction method.
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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 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 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