Image reconstruction from projections of digital breast tomosynthesis using deep learning

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorDe Paula, Davi D. [UNESP]-
Autor(es): dc.creatorSalvadeo, Denis H. P. [UNESP]-
Autor(es): dc.creatorDe Araújo, Darlan M. N. [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:46:18Z-
Data de disponibilização: dc.date.available2022-02-22T00:46:18Z-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2020-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1117/12.2582183-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/206153-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/206153-
Descrição: dc.descriptionThe Filtered Backprojection (FBP) algorithm for Computed Tomography (CT) reconstruction can be mapped entire in an Artificial Neural Network (ANN), with the backprojection (BP) operation simulated analytically in a layer and the Ram-Lak filter simulated as a convolutional layer. Thus, this work adapts the BP layer for Digital Breast Tomosynthesis (DBT) reconstruction, making possible the use of FBP simulated as an ANN to reconstruct DBT images. We showed that making the Ram-Lak layer trainable, the reconstructed image can be improved in terms of noise reduction. Finally, this study enables additional proposals of ANN with Deep Learning models for DBT reconstruction and denoising.-
Descrição: dc.descriptionASao Paulo State University (Unesp) Institute of Geosciences and Exact Sciences-
Descrição: dc.descriptionASao Paulo State University (Unesp) Institute of Geosciences and Exact Sciences-
Idioma: dc.languageen-
Relação: dc.relationProgress in Biomedical Optics and Imaging - Proceedings of SPIE-
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Palavras-chave: dc.subjectDeep learning-
Palavras-chave: dc.subjectDigital breast tomosynthesis-
Palavras-chave: dc.subjectNoise reduction-
Palavras-chave: dc.subjectTomographic reconstruction-
Título: dc.titleImage reconstruction from projections of digital breast tomosynthesis using deep learning-
Aparece nas coleções:Repositório Institucional - Unesp

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