An automated tissue-to-diagnosis pipeline using intraoperative stimulated Raman histology and deep learning

We recently developed and validated a bedside tissue-to-diagnosis pipeline using stimulated Raman histology (SRH), a label-free optical imaging method, and deep convolutional neural networks (CNN) in prospective clinical trial. Our CNN learned a hierarchy of interpretable histologic features found i...

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Detalles Bibliográficos
Autores principales: Hollon, Todd C., Orringer, Daniel A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Author's Views
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7199763/
https://www.ncbi.nlm.nih.gov/pubmed/32391430
http://dx.doi.org/10.1080/23723556.2020.1736742
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author Hollon, Todd C.
Orringer, Daniel A.
author_facet Hollon, Todd C.
Orringer, Daniel A.
author_sort Hollon, Todd C.
collection PubMed
description We recently developed and validated a bedside tissue-to-diagnosis pipeline using stimulated Raman histology (SRH), a label-free optical imaging method, and deep convolutional neural networks (CNN) in prospective clinical trial. Our CNN learned a hierarchy of interpretable histologic features found in the most common brain tumors and was able to accurately segment cancerous regions in SRH images.
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spelling pubmed-71997632020-09-28 An automated tissue-to-diagnosis pipeline using intraoperative stimulated Raman histology and deep learning Hollon, Todd C. Orringer, Daniel A. Mol Cell Oncol Author's Views We recently developed and validated a bedside tissue-to-diagnosis pipeline using stimulated Raman histology (SRH), a label-free optical imaging method, and deep convolutional neural networks (CNN) in prospective clinical trial. Our CNN learned a hierarchy of interpretable histologic features found in the most common brain tumors and was able to accurately segment cancerous regions in SRH images. Taylor & Francis 2020-04-01 /pmc/articles/PMC7199763/ /pubmed/32391430 http://dx.doi.org/10.1080/23723556.2020.1736742 Text en © 2020 The Author(s). Published with license by Taylor & Francis Group, LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
spellingShingle Author's Views
Hollon, Todd C.
Orringer, Daniel A.
An automated tissue-to-diagnosis pipeline using intraoperative stimulated Raman histology and deep learning
title An automated tissue-to-diagnosis pipeline using intraoperative stimulated Raman histology and deep learning
title_full An automated tissue-to-diagnosis pipeline using intraoperative stimulated Raman histology and deep learning
title_fullStr An automated tissue-to-diagnosis pipeline using intraoperative stimulated Raman histology and deep learning
title_full_unstemmed An automated tissue-to-diagnosis pipeline using intraoperative stimulated Raman histology and deep learning
title_short An automated tissue-to-diagnosis pipeline using intraoperative stimulated Raman histology and deep learning
title_sort automated tissue-to-diagnosis pipeline using intraoperative stimulated raman histology and deep learning
topic Author's Views
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7199763/
https://www.ncbi.nlm.nih.gov/pubmed/32391430
http://dx.doi.org/10.1080/23723556.2020.1736742
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