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Communication Dans Un Congrès Année : 2005

Conjugate gradient Mojette reconstruction

Résumé

Iterative methods are now recognized as powerful tools to solve inverse problems such as tomographic reconstruction. In this paper, the main goal is to present a new reconstruction algorithm made from two components. An iterative algorithm, namely the Conjugate Gradient (CG) method, is used to solve the tomographic problem in the least square (LS) sense for our specific discrete Mojette geometry. The results are compared (with the same geometry) to the corresponding Mojette Filtered Back Projection (FBP) method. In the fist part of the paper, we recall the discrete geometry used to define the projection M and backprojection M* operators. In the second part, the CG algorithm is presented within the context of the Mojette geometry. Noise is then added onto these Mojette projections with respect to the sampling and reconstructions are performed. Finally the Toeplitz block Toeplitz (TBT) character of M*M is demonstrated.
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Dates et versions

hal-01500580 , version 1 (16-05-2017)

Identifiants

Citer

Myriam Servières, Jérôme Idier, Nicolas Normand, Jean-Pierre Guédon. Conjugate gradient Mojette reconstruction. SPIE Medical Imaging 2005 : Image Processing, Feb 2005, San Diego, CA, United States. pp.2067--2074, ⟨10.1117/12.593399⟩. ⟨hal-01500580⟩
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