Honeycomb Artifact Removal Using Convolutional Neural Network for Fiber Bundle Imaging

We present a new deep learning framework for removing honeycomb artifacts yielded by optical path blocking of cladding layers in fiber bundle imaging. The proposed framework, HAR-CNN, provides an end-to-end mapping from a raw fiber bundle image to an artifact-free image via a convolution neural netw...

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Detalles Bibliográficos
Autores principales: Kim, Eunchan, Kim, Seonghoon, Choi, Myunghwan, Seo, Taewon, Yang, Sungwook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824069/
https://www.ncbi.nlm.nih.gov/pubmed/36616931
http://dx.doi.org/10.3390/s23010333

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824069/
https://www.ncbi.nlm.nih.gov/pubmed/36616931
http://dx.doi.org/10.3390/s23010333

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