Stabilizing deep tomographic reconstruction: Part A. Hybrid framework and experimental results

A recent PNAS paper reveals that several popular deep reconstruction networks are unstable. Specifically, three kinds of instabilities were reported: (1) strong image artefacts from tiny perturbations, (2) small features missed in a deeply reconstructed image, and (3) decreased imaging performance w...

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Detalles Bibliográficos
Autores principales: Wu, Weiwen, Hu, Dianlin, Cong, Wenxiang, Shan, Hongming, Wang, Shaoyu, Niu, Chuang, Yan, Pingkun, Yu, Hengyong, Vardhanabhuti, Varut, Wang, Ge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122961/
https://www.ncbi.nlm.nih.gov/pubmed/35607623
http://dx.doi.org/10.1016/j.patter.2022.100474

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122961/
https://www.ncbi.nlm.nih.gov/pubmed/35607623
http://dx.doi.org/10.1016/j.patter.2022.100474

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