Deep learning for microscopy image enhancement and automated labelling

Ben Mills; Benita S. MacKay; Sophie Blundell; Olivia Etter; Yunhui Xie; Matthew F. Praeger; Michael McDonnell; Alex Courtier; Robert W. Eason; Rohan Lewis; James A. Grant-Jacob

doi:10.1117/12.2584826

4 October 2020 Deep learning for microscopy image enhancement and automated labelling

Ben Mills, Benita S. MacKay, Sophie Blundell, Olivia Etter, Yunhui Xie, Matthew F. Praeger, Michael McDonnell, Alex Courtier, Robert W. Eason, Rohan Lewis, James A. Grant-Jacob

Author Affiliations +

Proceedings Volume 11575, Biophotonics and Biomedical Microscopy; 1157505 (2020) https://doi.org/10.1117/12.2584826
Event: SPIE Photonex and Vacuum Expo, 2020, Online Only

Abstract

The interface of deep learning and imaging has seen extraordinary progress in the past few years as computational power now enables image processing that can exceed human capability. Much of the recent work at this interface involves the application of variants of convolutional neural networks, for a wide variety of techniques including image enhancement, style transfer and labelling. However, whilst deep learning can unlock extremely powerful capabilities, the collection and processing of appropriate training data remains a significant challenge. In this talk, a brief tutorial on the practical application of neural networks for image processing will be presented, followed by experimental results associated with optical and scanning electron microscopy. The focus of this talk will be on the demonstration of image enhancement of optical microscopy from 20x resolution to 1500x, whilst simultaneously identifying the objects present and hence enabling automated labelling, colour-enhancing and removal of specific objects in the magnified image.

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Citation Download Citation

Ben Mills, Benita S. MacKay, Sophie Blundell, Olivia Etter, Yunhui Xie, Matthew F. Praeger, Michael McDonnell, Alex Courtier, Robert W. Eason, Rohan Lewis, and James A. Grant-Jacob "Deep learning for microscopy image enhancement and automated labelling", Proc. SPIE 11575, Biophotonics and Biomedical Microscopy, 1157505 (4 October 2020); https://doi.org/10.1117/12.2584826

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