Fiber Bundle Image Reconstruction Using Convolutional Neural Networks and Bundle Rotation in Endomicroscopy

Fiber-bundle endomicroscopy has several recognized drawbacks, the most prominent being the honeycomb effect. We developed a multi-frame super-resolution algorithm exploiting bundle rotation to extract features and reconstruct underlying tissue. Simulated data was used with rotated fiber-bundle masks...

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Detalles Bibliográficos
Autores principales: Eadie, Matthew, Liao, Jinpeng, Ageeli, Wael, Nabi, Ghulam, Krstajić, Nikola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007631/
https://www.ncbi.nlm.nih.gov/pubmed/36904673
http://dx.doi.org/10.3390/s23052469

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007631/
https://www.ncbi.nlm.nih.gov/pubmed/36904673
http://dx.doi.org/10.3390/s23052469

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