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Artificial Intelligence Assists in the Detection of Blood Vessels in Whole Slide Images: Practical Benefits for Oncological Pathology

The analysis of the microvasculature and the assessment of angiogenesis have significant prognostic value in various diseases, including cancer. The search for invasion into the blood and lymphatic vessels and the assessment of angiogenesis are important aspects of oncological diagnosis. These featu...

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Autores principales: Timakova, Anna, Ananev, Vladislav, Fayzullin, Alexey, Makarov, Vladimir, Ivanova, Elena, Shekhter, Anatoly, Timashev, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10526383/
https://www.ncbi.nlm.nih.gov/pubmed/37759727
http://dx.doi.org/10.3390/biom13091327
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author Timakova, Anna
Ananev, Vladislav
Fayzullin, Alexey
Makarov, Vladimir
Ivanova, Elena
Shekhter, Anatoly
Timashev, Peter
author_facet Timakova, Anna
Ananev, Vladislav
Fayzullin, Alexey
Makarov, Vladimir
Ivanova, Elena
Shekhter, Anatoly
Timashev, Peter
author_sort Timakova, Anna
collection PubMed
description The analysis of the microvasculature and the assessment of angiogenesis have significant prognostic value in various diseases, including cancer. The search for invasion into the blood and lymphatic vessels and the assessment of angiogenesis are important aspects of oncological diagnosis. These features determine the prognosis and aggressiveness of the tumor. Traditional manual evaluation methods are time consuming and subject to inter-observer variability. Blood vessel detection is a perfect task for artificial intelligence, which is capable of rapid analyzing thousands of tissue structures in whole slide images. The development of computer vision solutions requires the segmentation of tissue regions, the extraction of features and the training of machine learning models. In this review, we focus on the methodologies employed by researchers to identify blood vessels and vascular invasion across a range of tumor localizations, including breast, lung, colon, brain, renal, pancreatic, gastric and oral cavity cancers. Contemporary models herald a new era of computational pathology in morphological diagnostics.
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spelling pubmed-105263832023-09-28 Artificial Intelligence Assists in the Detection of Blood Vessels in Whole Slide Images: Practical Benefits for Oncological Pathology Timakova, Anna Ananev, Vladislav Fayzullin, Alexey Makarov, Vladimir Ivanova, Elena Shekhter, Anatoly Timashev, Peter Biomolecules Review The analysis of the microvasculature and the assessment of angiogenesis have significant prognostic value in various diseases, including cancer. The search for invasion into the blood and lymphatic vessels and the assessment of angiogenesis are important aspects of oncological diagnosis. These features determine the prognosis and aggressiveness of the tumor. Traditional manual evaluation methods are time consuming and subject to inter-observer variability. Blood vessel detection is a perfect task for artificial intelligence, which is capable of rapid analyzing thousands of tissue structures in whole slide images. The development of computer vision solutions requires the segmentation of tissue regions, the extraction of features and the training of machine learning models. In this review, we focus on the methodologies employed by researchers to identify blood vessels and vascular invasion across a range of tumor localizations, including breast, lung, colon, brain, renal, pancreatic, gastric and oral cavity cancers. Contemporary models herald a new era of computational pathology in morphological diagnostics. MDPI 2023-08-29 /pmc/articles/PMC10526383/ /pubmed/37759727 http://dx.doi.org/10.3390/biom13091327 Text en © 2023 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
Timakova, Anna
Ananev, Vladislav
Fayzullin, Alexey
Makarov, Vladimir
Ivanova, Elena
Shekhter, Anatoly
Timashev, Peter
Artificial Intelligence Assists in the Detection of Blood Vessels in Whole Slide Images: Practical Benefits for Oncological Pathology
title Artificial Intelligence Assists in the Detection of Blood Vessels in Whole Slide Images: Practical Benefits for Oncological Pathology
title_full Artificial Intelligence Assists in the Detection of Blood Vessels in Whole Slide Images: Practical Benefits for Oncological Pathology
title_fullStr Artificial Intelligence Assists in the Detection of Blood Vessels in Whole Slide Images: Practical Benefits for Oncological Pathology
title_full_unstemmed Artificial Intelligence Assists in the Detection of Blood Vessels in Whole Slide Images: Practical Benefits for Oncological Pathology
title_short Artificial Intelligence Assists in the Detection of Blood Vessels in Whole Slide Images: Practical Benefits for Oncological Pathology
title_sort artificial intelligence assists in the detection of blood vessels in whole slide images: practical benefits for oncological pathology
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10526383/
https://www.ncbi.nlm.nih.gov/pubmed/37759727
http://dx.doi.org/10.3390/biom13091327
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