Time-frequency time-space long short-term memory networks for image classification of histopathological tissue

Abstract Image analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discovery. Particularly for cancer research, precise classification of histopathological images is the ultimate objective of the image analysis. Here...

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Autor principal:	Tuan D. Pham
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e6e6d54865f14d7988830a92e14f3ebc
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spelling	oai:doaj.org-article:e6e6d54865f14d7988830a92e14f3ebc2021-12-02T16:10:37ZTime-frequency time-space long short-term memory networks for image classification of histopathological tissue10.1038/s41598-021-93160-52045-2322https://doaj.org/article/e6e6d54865f14d7988830a92e14f3ebc2021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93160-5https://doaj.org/toc/2045-2322Abstract Image analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discovery. Particularly for cancer research, precise classification of histopathological images is the ultimate objective of the image analysis. Here, the time-frequency time-space long short-term memory network (TF-TS LSTM) developed for classification of time series is applied for classifying histopathological images. The deep learning is empowered by the use of sequential time-frequency and time-space features extracted from the images. Furthermore, unlike conventional classification practice, a strategy for class modeling is designed to leverage the learning power of the TF-TS LSTM. Tests on several datasets of histopathological images of haematoxylin-and-eosin and immunohistochemistry stains demonstrate the strong capability of the artificial intelligence (AI)-based approach for producing very accurate classification results. The proposed approach has the potential to be an AI tool for robust classification of histopathological images.Tuan D. PhamNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tuan D. Pham Time-frequency time-space long short-term memory networks for image classification of histopathological tissue
description	Abstract Image analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discovery. Particularly for cancer research, precise classification of histopathological images is the ultimate objective of the image analysis. Here, the time-frequency time-space long short-term memory network (TF-TS LSTM) developed for classification of time series is applied for classifying histopathological images. The deep learning is empowered by the use of sequential time-frequency and time-space features extracted from the images. Furthermore, unlike conventional classification practice, a strategy for class modeling is designed to leverage the learning power of the TF-TS LSTM. Tests on several datasets of histopathological images of haematoxylin-and-eosin and immunohistochemistry stains demonstrate the strong capability of the artificial intelligence (AI)-based approach for producing very accurate classification results. The proposed approach has the potential to be an AI tool for robust classification of histopathological images.
format	article
author	Tuan D. Pham
author_facet	Tuan D. Pham
author_sort	Tuan D. Pham
title	Time-frequency time-space long short-term memory networks for image classification of histopathological tissue
title_short	Time-frequency time-space long short-term memory networks for image classification of histopathological tissue
title_full	Time-frequency time-space long short-term memory networks for image classification of histopathological tissue
title_fullStr	Time-frequency time-space long short-term memory networks for image classification of histopathological tissue
title_full_unstemmed	Time-frequency time-space long short-term memory networks for image classification of histopathological tissue
title_sort	time-frequency time-space long short-term memory networks for image classification of histopathological tissue
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/e6e6d54865f14d7988830a92e14f3ebc
work_keys_str_mv	AT tuandpham timefrequencytimespacelongshorttermmemorynetworksforimageclassificationofhistopathologicaltissue
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Time-frequency time-space long short-term memory networks for image classification of histopathological tissue

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