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Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images: A Survey
Hepatic vessel skeletonization serves as an important means of hepatic vascular analysis and vessel segmentation. This paper presents a survey of techniques and algorithms for hepatic vessel skeletonization in medical images. We summarized the latest developments and classical approaches in this fie...
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/PMC9031516/ https://www.ncbi.nlm.nih.gov/pubmed/35455128 http://dx.doi.org/10.3390/e24040465 |
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author | Zhang, Jianfeng Wu, Fa Chang, Wanru Kong, Dexing |
author_facet | Zhang, Jianfeng Wu, Fa Chang, Wanru Kong, Dexing |
author_sort | Zhang, Jianfeng |
collection | PubMed |
description | Hepatic vessel skeletonization serves as an important means of hepatic vascular analysis and vessel segmentation. This paper presents a survey of techniques and algorithms for hepatic vessel skeletonization in medical images. We summarized the latest developments and classical approaches in this field. These methods are classified into five categories according to their methodological characteristics. The overview and brief assessment of each category are provided in the corresponding chapters, respectively. We provide a comprehensive summary among the cited publications, image modalities and datasets from various aspects, which hope to reveal the pros and cons of every method, summarize its achievements and discuss the challenges and future trends. |
format | Online Article Text |
id | pubmed-9031516 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90315162022-04-23 Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images: A Survey Zhang, Jianfeng Wu, Fa Chang, Wanru Kong, Dexing Entropy (Basel) Review Hepatic vessel skeletonization serves as an important means of hepatic vascular analysis and vessel segmentation. This paper presents a survey of techniques and algorithms for hepatic vessel skeletonization in medical images. We summarized the latest developments and classical approaches in this field. These methods are classified into five categories according to their methodological characteristics. The overview and brief assessment of each category are provided in the corresponding chapters, respectively. We provide a comprehensive summary among the cited publications, image modalities and datasets from various aspects, which hope to reveal the pros and cons of every method, summarize its achievements and discuss the challenges and future trends. MDPI 2022-03-28 /pmc/articles/PMC9031516/ /pubmed/35455128 http://dx.doi.org/10.3390/e24040465 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 Zhang, Jianfeng Wu, Fa Chang, Wanru Kong, Dexing Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images: A Survey |
title | Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images: A Survey |
title_full | Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images: A Survey |
title_fullStr | Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images: A Survey |
title_full_unstemmed | Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images: A Survey |
title_short | Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images: A Survey |
title_sort | techniques and algorithms for hepatic vessel skeletonization in medical images: a survey |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9031516/ https://www.ncbi.nlm.nih.gov/pubmed/35455128 http://dx.doi.org/10.3390/e24040465 |
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