Cargando…
Deep Learning for Whole Slide Image Analysis: An Overview
The widespread adoption of whole slide imaging has increased the demand for effective and efficient gigapixel image analysis. Deep learning is at the forefront of computer vision, showcasing significant improvements over previous methodologies on visual understanding. However, whole slide images hav...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6882930/ https://www.ncbi.nlm.nih.gov/pubmed/31824952 http://dx.doi.org/10.3389/fmed.2019.00264 |
_version_ | 1783474271072288768 |
---|---|
author | Dimitriou, Neofytos Arandjelović, Ognjen Caie, Peter D. |
author_facet | Dimitriou, Neofytos Arandjelović, Ognjen Caie, Peter D. |
author_sort | Dimitriou, Neofytos |
collection | PubMed |
description | The widespread adoption of whole slide imaging has increased the demand for effective and efficient gigapixel image analysis. Deep learning is at the forefront of computer vision, showcasing significant improvements over previous methodologies on visual understanding. However, whole slide images have billions of pixels and suffer from high morphological heterogeneity as well as from different types of artifacts. Collectively, these impede the conventional use of deep learning. For the clinical translation of deep learning solutions to become a reality, these challenges need to be addressed. In this paper, we review work on the interdisciplinary attempt of training deep neural networks using whole slide images, and highlight the different ideas underlying these methodologies. |
format | Online Article Text |
id | pubmed-6882930 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68829302019-12-10 Deep Learning for Whole Slide Image Analysis: An Overview Dimitriou, Neofytos Arandjelović, Ognjen Caie, Peter D. Front Med (Lausanne) Medicine The widespread adoption of whole slide imaging has increased the demand for effective and efficient gigapixel image analysis. Deep learning is at the forefront of computer vision, showcasing significant improvements over previous methodologies on visual understanding. However, whole slide images have billions of pixels and suffer from high morphological heterogeneity as well as from different types of artifacts. Collectively, these impede the conventional use of deep learning. For the clinical translation of deep learning solutions to become a reality, these challenges need to be addressed. In this paper, we review work on the interdisciplinary attempt of training deep neural networks using whole slide images, and highlight the different ideas underlying these methodologies. Frontiers Media S.A. 2019-11-22 /pmc/articles/PMC6882930/ /pubmed/31824952 http://dx.doi.org/10.3389/fmed.2019.00264 Text en Copyright © 2019 Dimitriou, Arandjelović and Caie. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Medicine Dimitriou, Neofytos Arandjelović, Ognjen Caie, Peter D. Deep Learning for Whole Slide Image Analysis: An Overview |
title | Deep Learning for Whole Slide Image Analysis: An Overview |
title_full | Deep Learning for Whole Slide Image Analysis: An Overview |
title_fullStr | Deep Learning for Whole Slide Image Analysis: An Overview |
title_full_unstemmed | Deep Learning for Whole Slide Image Analysis: An Overview |
title_short | Deep Learning for Whole Slide Image Analysis: An Overview |
title_sort | deep learning for whole slide image analysis: an overview |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6882930/ https://www.ncbi.nlm.nih.gov/pubmed/31824952 http://dx.doi.org/10.3389/fmed.2019.00264 |
work_keys_str_mv | AT dimitriouneofytos deeplearningforwholeslideimageanalysisanoverview AT arandjelovicognjen deeplearningforwholeslideimageanalysisanoverview AT caiepeterd deeplearningforwholeslideimageanalysisanoverview |