Deep learning a boon for biophotonics?
Pradhan P, Guo S, Ryabchykov O, Popp J, Bocklitz TW (2020)
Publication Type: Journal article, Review article
Publication year: 2020
Journal
Book Volume: 13
Article Number: e201960186
Journal Issue: 6
Abstract
This review covers original articles using deep learning in the biophotonic field published in the last years. In these years deep learning, which is a subset of machine learning mostly based on artificial neural network geometries, was applied to a number of biophotonic tasks and has achieved state-of-the-art performances. Therefore, deep learning in the biophotonic field is rapidly growing and it will be utilized in the next years to obtain real-time biophotonic decision-making systems and to analyze biophotonic data in general. In this contribution, we discuss the possibilities of deep learning in the biophotonic field including image classification, segmentation, registration, pseudostaining and resolution enhancement. Additionally, we discuss the potential use of deep learning for spectroscopic data including spectral data preprocessing and spectral classification. We conclude this review by addressing the potential applications and challenges of using deep learning for biophotonic data.
Involved external institutions
Germany (DE)How to cite
APA:
Pradhan, P., Guo, S., Ryabchykov, O., Popp, J., & Bocklitz, T.W. (2020). Deep learning a boon for biophotonics? Journal of Biophotonics, 13(6). https://doi.org/10.1002/jbio.201960186
MLA:
Pradhan, Pranita, et al. "Deep learning a boon for biophotonics?" Journal of Biophotonics 13.6 (2020).
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