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Tomographic Image Reconstruction of Fan-Beam Projections with Equidistant Detectors using Partially Connected Neural Networks
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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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2003
Tomographic Image Reconstruction of Fan-Beam Projections with Equidistant Detectors using Partially Connected Neural Networks
Artificial Intelligence
Neural Nets
Ribeiro
Eduardo Parente
Eduardo Parente Ribeiro
Silva
Hamilton Pereira da
Hamilton Pereira da Silva
Medeiros
Luciano Frontino de
Luciano Frontino de Medeiros
Learning and Nonlinear Models – Revista da Sociedade Brasileira de Redes Neurais