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7 March 2022 Transformation of H and E stained tissue into special stains using deep learning
Kevin De Haan, Yijie Zhang, Jonathan E. Zuckerman, Tairan Liu, Yair Rivenson, W. Dean Wallace, Aydogan Ozcan
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Proceedings Volume PC11954, Optical Biopsy XX: Toward Real-Time Spectroscopic Imaging and Diagnosis; PC119540D (2022) https://doi.org/10.1117/12.2607987
Event: SPIE BiOS, 2022, San Francisco, California, United States
Abstract
We present a supervised learning approach to train a deep neural network which can transform images of H&E stained tissue sections into special stains (e.g., PAS, Jones silver stain and Masson’s Trichrome). We performed a diagnostic study using tissue sections from 58 subjects covering a variety of non-neoplastic kidney diseases to show that when the pathologists performed their diagnoses using the three virtually-created special stains in addition to H&E, a statistically significant diagnostic improvement was made over the use of H&E only. This virtual staining technique can be used to improve preliminary diagnoses while saving time and reducing costs.
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Kevin De Haan, Yijie Zhang, Jonathan E. Zuckerman, Tairan Liu, Yair Rivenson, W. Dean Wallace, and Aydogan Ozcan "Transformation of H and E stained tissue into special stains using deep learning", Proc. SPIE PC11954, Optical Biopsy XX: Toward Real-Time Spectroscopic Imaging and Diagnosis, PC119540D (7 March 2022); https://doi.org/10.1117/12.2607987
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KEYWORDS
Tissues
Diagnostics
Biopsy
Kidney
Silver
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