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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cet article présente un algorithme de rétro-propagation neuronale permettant de reconstruire des images CT bidimensionnelles à partir d'un petit nombre de données de projection. L'article étend les travaux de [1], dans lesquels un algorithme de rétropropagation est appliqué au problème de reconstruction d'images CT. La règle delta de l'algorithme de rétropropagation ordinaire est modifiée à l'aide d'un signal d'apprentissage « secondaire » et du schéma de « rétropropagation résiliente ». Les résultats obtenus sont présentés avec ceux de deux méthodes conventionnelles bien connues : la méthode MART et la méthode EMML. Une évaluation quantitative révèle l'efficacité de l'algorithme proposé.
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Fath El Alem F. ALI, Zensho NAKAO, Yen-Wei CHEN, Kazunori MATSUO, Izuru OHKAWA, "An Adaptive Backpropagation Algorithm for Limited-Angle CT Image Reconstruction" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 6, pp. 1049-1058, June 2000, doi: .
Abstract: Presented in this paper is a neural back propagation algorithm for reconstructing two-dimensional CT images from a small number of projection data. The paper extends the work in [1], in which a backpropagation algorithm is applied to the CT image reconstruction problem. The delta rule of the ordinary backpropagation algorithm is modified using a 'secondary' teaching signal and the 'Resilient backpropagation' scheme. Results obtained are presented along with those of two well known conventional methods: MART and EMML method. A quantitative evaluation reveals the effectiveness of the proposed algorithm.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_6_1049/_p
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@ARTICLE{e83-a_6_1049,
author={Fath El Alem F. ALI, Zensho NAKAO, Yen-Wei CHEN, Kazunori MATSUO, Izuru OHKAWA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Adaptive Backpropagation Algorithm for Limited-Angle CT Image Reconstruction},
year={2000},
volume={E83-A},
number={6},
pages={1049-1058},
abstract={Presented in this paper is a neural back propagation algorithm for reconstructing two-dimensional CT images from a small number of projection data. The paper extends the work in [1], in which a backpropagation algorithm is applied to the CT image reconstruction problem. The delta rule of the ordinary backpropagation algorithm is modified using a 'secondary' teaching signal and the 'Resilient backpropagation' scheme. Results obtained are presented along with those of two well known conventional methods: MART and EMML method. A quantitative evaluation reveals the effectiveness of the proposed algorithm.},
keywords={},
doi={},
ISSN={},
month={June},}
Copier
TY - JOUR
TI - An Adaptive Backpropagation Algorithm for Limited-Angle CT Image Reconstruction
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1049
EP - 1058
AU - Fath El Alem F. ALI
AU - Zensho NAKAO
AU - Yen-Wei CHEN
AU - Kazunori MATSUO
AU - Izuru OHKAWA
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2000
AB - Presented in this paper is a neural back propagation algorithm for reconstructing two-dimensional CT images from a small number of projection data. The paper extends the work in [1], in which a backpropagation algorithm is applied to the CT image reconstruction problem. The delta rule of the ordinary backpropagation algorithm is modified using a 'secondary' teaching signal and the 'Resilient backpropagation' scheme. Results obtained are presented along with those of two well known conventional methods: MART and EMML method. A quantitative evaluation reveals the effectiveness of the proposed algorithm.
ER -