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Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects
Digital imaging and advanced microscopy play a pivotal role in the diagnosis of kidney diseases. In recent years, great achievements have been made in digital imaging, providing novel approaches for precise quantitative assessments of nephropathology and relieving burdens of renal pathologists. Deve...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410196/ https://www.ncbi.nlm.nih.gov/pubmed/36013157 http://dx.doi.org/10.3390/jcm11164918 |
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author | Wang, Yiqin Wen, Qiong Jin, Luhua Chen, Wei |
author_facet | Wang, Yiqin Wen, Qiong Jin, Luhua Chen, Wei |
author_sort | Wang, Yiqin |
collection | PubMed |
description | Digital imaging and advanced microscopy play a pivotal role in the diagnosis of kidney diseases. In recent years, great achievements have been made in digital imaging, providing novel approaches for precise quantitative assessments of nephropathology and relieving burdens of renal pathologists. Developing novel methods of artificial intelligence (AI)-assisted technology through multidisciplinary interaction among computer engineers, renal specialists, and nephropathologists could prove beneficial for renal pathology diagnoses. An increasing number of publications has demonstrated the rapid growth of AI-based technology in nephrology. In this review, we offer an overview of AI-assisted renal pathology, including AI concepts and the workflow of processing digital image data, focusing on the impressive advances of AI application in disease-specific backgrounds. In particular, this review describes the applied computer vision algorithms for the segmentation of kidney structures, diagnosis of specific pathological changes, and prognosis prediction based on images. Lastly, we discuss challenges and prospects to provide an objective view of this topic. |
format | Online Article Text |
id | pubmed-9410196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94101962022-08-26 Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects Wang, Yiqin Wen, Qiong Jin, Luhua Chen, Wei J Clin Med Review Digital imaging and advanced microscopy play a pivotal role in the diagnosis of kidney diseases. In recent years, great achievements have been made in digital imaging, providing novel approaches for precise quantitative assessments of nephropathology and relieving burdens of renal pathologists. Developing novel methods of artificial intelligence (AI)-assisted technology through multidisciplinary interaction among computer engineers, renal specialists, and nephropathologists could prove beneficial for renal pathology diagnoses. An increasing number of publications has demonstrated the rapid growth of AI-based technology in nephrology. In this review, we offer an overview of AI-assisted renal pathology, including AI concepts and the workflow of processing digital image data, focusing on the impressive advances of AI application in disease-specific backgrounds. In particular, this review describes the applied computer vision algorithms for the segmentation of kidney structures, diagnosis of specific pathological changes, and prognosis prediction based on images. Lastly, we discuss challenges and prospects to provide an objective view of this topic. MDPI 2022-08-22 /pmc/articles/PMC9410196/ /pubmed/36013157 http://dx.doi.org/10.3390/jcm11164918 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Wang, Yiqin Wen, Qiong Jin, Luhua Chen, Wei Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects |
title | Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects |
title_full | Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects |
title_fullStr | Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects |
title_full_unstemmed | Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects |
title_short | Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects |
title_sort | artificial intelligence-assisted renal pathology: advances and prospects |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410196/ https://www.ncbi.nlm.nih.gov/pubmed/36013157 http://dx.doi.org/10.3390/jcm11164918 |
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