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Artificial intelligence and its applications in digital hematopathology

The advent of whole-slide imaging, faster image data generation, and cheaper forms of data storage have made it easier for pathologists to manipulate digital slide images and interpret more detailed biological processes in conjunction with clinical samples. In parallel, with continuous breakthroughs...

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Autores principales: Hu, Yongfei, Luo, Yinglun, Tang, Guangjue, Huang, Yan, Kang, Juanjuan, Wang, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9742095/
https://www.ncbi.nlm.nih.gov/pubmed/36518598
http://dx.doi.org/10.1097/BS9.0000000000000130
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author Hu, Yongfei
Luo, Yinglun
Tang, Guangjue
Huang, Yan
Kang, Juanjuan
Wang, Dong
author_facet Hu, Yongfei
Luo, Yinglun
Tang, Guangjue
Huang, Yan
Kang, Juanjuan
Wang, Dong
author_sort Hu, Yongfei
collection PubMed
description The advent of whole-slide imaging, faster image data generation, and cheaper forms of data storage have made it easier for pathologists to manipulate digital slide images and interpret more detailed biological processes in conjunction with clinical samples. In parallel, with continuous breakthroughs in object detection, image feature extraction, image classification and image segmentation, artificial intelligence (AI) is becoming the most beneficial technology for high-throughput analysis of image data in various biomedical imaging disciplines. Integrating digital images into biological workflows, advanced algorithms, and computer vision techniques expands the biologist’s horizons beyond the microscope slide. Here, we introduce recent developments in AI applied to microscopy in hematopathology. We give an overview of its concepts and present its applications in normal or abnormal hematopoietic cells identification. We discuss how AI shows great potential to push the limits of microscopy and enhance the resolution, signal and information content of acquired data. Its shortcomings are discussed, as well as future directions for the field.
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spelling pubmed-97420952022-12-13 Artificial intelligence and its applications in digital hematopathology Hu, Yongfei Luo, Yinglun Tang, Guangjue Huang, Yan Kang, Juanjuan Wang, Dong Blood Sci Special Issue: RNA and Hematopoiesis The advent of whole-slide imaging, faster image data generation, and cheaper forms of data storage have made it easier for pathologists to manipulate digital slide images and interpret more detailed biological processes in conjunction with clinical samples. In parallel, with continuous breakthroughs in object detection, image feature extraction, image classification and image segmentation, artificial intelligence (AI) is becoming the most beneficial technology for high-throughput analysis of image data in various biomedical imaging disciplines. Integrating digital images into biological workflows, advanced algorithms, and computer vision techniques expands the biologist’s horizons beyond the microscope slide. Here, we introduce recent developments in AI applied to microscopy in hematopathology. We give an overview of its concepts and present its applications in normal or abnormal hematopoietic cells identification. We discuss how AI shows great potential to push the limits of microscopy and enhance the resolution, signal and information content of acquired data. Its shortcomings are discussed, as well as future directions for the field. Lippincott Williams & Wilkins 2022-07-14 /pmc/articles/PMC9742095/ /pubmed/36518598 http://dx.doi.org/10.1097/BS9.0000000000000130 Text en Copyright © 2022 The Authors. Published by Wolters Kluwer Health Inc., on behalf of the Chinese Medical Association (CMA) and Institute of Hematology, Chinese Academy of Medical Sciences & Peking Union Medical College (IHCAMS). https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Special Issue: RNA and Hematopoiesis
Hu, Yongfei
Luo, Yinglun
Tang, Guangjue
Huang, Yan
Kang, Juanjuan
Wang, Dong
Artificial intelligence and its applications in digital hematopathology
title Artificial intelligence and its applications in digital hematopathology
title_full Artificial intelligence and its applications in digital hematopathology
title_fullStr Artificial intelligence and its applications in digital hematopathology
title_full_unstemmed Artificial intelligence and its applications in digital hematopathology
title_short Artificial intelligence and its applications in digital hematopathology
title_sort artificial intelligence and its applications in digital hematopathology
topic Special Issue: RNA and Hematopoiesis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9742095/
https://www.ncbi.nlm.nih.gov/pubmed/36518598
http://dx.doi.org/10.1097/BS9.0000000000000130
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