@misc{cogprints6085,
          volume = {1},
          number = {2},
           title = {Tomographic Image Reconstruction of Fan-Beam Projections with Equidistant Detectors using Partially Connected Neural Networks},
          author = {Luciano Frontino de Medeiros and Hamilton Pereira da Silva and Eduardo Parente Ribeiro},
            year = {2003},
           pages = {122--130},
         journal = {Learning and Nonlinear Models ? Revista da Sociedade Brasileira de Redes Neurais},
        keywords = {tomography, reconstruction, neural network, fan-beam, interpolation},
             url = {http://cogprints.org/6085/},
        abstract = {We present a neural network approach for tomographic imaging problem using interpolation methods and fan-beam projections. This approach uses a partially connected neural network especially assembled for solving tomographic
reconstruction with no need of training. We extended the calculations to perform reconstruction with interpolation and to allow tomography of fan-beam geometry. The main goal is to aggregate speed while maintaining or improving the quality of the tomographic reconstruction process.}
}

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