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16 March 2023 Deep-learning enables rapid and slide-free cellular imaging with virtual histological staining: from two-dimensional to three-dimensional histopathology (Conference Presentation)
Terence T. W. Wong
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Proceedings Volume PC12390, High-Speed Biomedical Imaging and Spectroscopy VIII; PC1239004 (2023) https://doi.org/10.1117/12.2653179
Event: SPIE BiOS, 2023, San Francisco, California, United States
Abstract
Rapid and slide-free cellular imaging with histological contrast and minimal tissue preparation has long been a challenging and yet appealing medical pursuit. We have recently proposed a promising and transformative histological imaging method, coined computational high-throughput autofluorescence microscopy by pattern illumination (CHAMP), which can provide rapid and label-free imaging of thick and unprocessed tissues with large surface irregularity at an acquisition speed of 10 mm^2/10 s with 1.1-µm lateral resolution. CHAMP images can be subsequently transformed into virtually stained histological images (Deep-CHAMP) through unsupervised learning. By incorporating a sectioning vibratome with a similar system configuration, three-dimensional histopathology is also feasible.
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Terence T. W. Wong "Deep-learning enables rapid and slide-free cellular imaging with virtual histological staining: from two-dimensional to three-dimensional histopathology (Conference Presentation)", Proc. SPIE PC12390, High-Speed Biomedical Imaging and Spectroscopy VIII, PC1239004 (16 March 2023); https://doi.org/10.1117/12.2653179
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KEYWORDS
3D image processing
Tissues
3D acquisition
Image resolution
Machine learning
Microscopy
Natural surfaces
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