@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.} }