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Practical utility of liver segmentation methods in clinical surgeries and interventions

Clinical imaging (e.g., magnetic resonance imaging and computed tomography) is a crucial adjunct for clinicians, aiding in the diagnosis of diseases and planning of appropriate interventions. This is especially true in malignant conditions such as hepatocellular carcinoma (HCC), where image segmenta...

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Autores principales: Ansari, Mohammed Yusuf, Abdalla, Alhusain, Ansari, Mohammed Yaqoob, Ansari, Mohammed Ishaq, Malluhi, Byanne, Mohanty, Snigdha, Mishra, Subhashree, Singh, Sudhansu Sekhar, Abinahed, Julien, Al-Ansari, Abdulla, Balakrishnan, Shidin, Dakua, Sarada Prasad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9128093/
https://www.ncbi.nlm.nih.gov/pubmed/35610600
http://dx.doi.org/10.1186/s12880-022-00825-2
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author Ansari, Mohammed Yusuf
Abdalla, Alhusain
Ansari, Mohammed Yaqoob
Ansari, Mohammed Ishaq
Malluhi, Byanne
Mohanty, Snigdha
Mishra, Subhashree
Singh, Sudhansu Sekhar
Abinahed, Julien
Al-Ansari, Abdulla
Balakrishnan, Shidin
Dakua, Sarada Prasad
author_facet Ansari, Mohammed Yusuf
Abdalla, Alhusain
Ansari, Mohammed Yaqoob
Ansari, Mohammed Ishaq
Malluhi, Byanne
Mohanty, Snigdha
Mishra, Subhashree
Singh, Sudhansu Sekhar
Abinahed, Julien
Al-Ansari, Abdulla
Balakrishnan, Shidin
Dakua, Sarada Prasad
author_sort Ansari, Mohammed Yusuf
collection PubMed
description Clinical imaging (e.g., magnetic resonance imaging and computed tomography) is a crucial adjunct for clinicians, aiding in the diagnosis of diseases and planning of appropriate interventions. This is especially true in malignant conditions such as hepatocellular carcinoma (HCC), where image segmentation (such as accurate delineation of liver and tumor) is the preliminary step taken by the clinicians to optimize diagnosis, staging, and treatment planning and intervention (e.g., transplantation, surgical resection, radiotherapy, PVE, embolization, etc). Thus, segmentation methods could potentially impact the diagnosis and treatment outcomes. This paper comprehensively reviews the literature (during the year 2012–2021) for relevant segmentation methods and proposes a broad categorization based on their clinical utility (i.e., surgical and radiological interventions) in HCC. The categorization is based on the parameters such as precision, accuracy, and automation.
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spelling pubmed-91280932022-05-25 Practical utility of liver segmentation methods in clinical surgeries and interventions Ansari, Mohammed Yusuf Abdalla, Alhusain Ansari, Mohammed Yaqoob Ansari, Mohammed Ishaq Malluhi, Byanne Mohanty, Snigdha Mishra, Subhashree Singh, Sudhansu Sekhar Abinahed, Julien Al-Ansari, Abdulla Balakrishnan, Shidin Dakua, Sarada Prasad BMC Med Imaging Research Clinical imaging (e.g., magnetic resonance imaging and computed tomography) is a crucial adjunct for clinicians, aiding in the diagnosis of diseases and planning of appropriate interventions. This is especially true in malignant conditions such as hepatocellular carcinoma (HCC), where image segmentation (such as accurate delineation of liver and tumor) is the preliminary step taken by the clinicians to optimize diagnosis, staging, and treatment planning and intervention (e.g., transplantation, surgical resection, radiotherapy, PVE, embolization, etc). Thus, segmentation methods could potentially impact the diagnosis and treatment outcomes. This paper comprehensively reviews the literature (during the year 2012–2021) for relevant segmentation methods and proposes a broad categorization based on their clinical utility (i.e., surgical and radiological interventions) in HCC. The categorization is based on the parameters such as precision, accuracy, and automation. BioMed Central 2022-05-24 /pmc/articles/PMC9128093/ /pubmed/35610600 http://dx.doi.org/10.1186/s12880-022-00825-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ansari, Mohammed Yusuf
Abdalla, Alhusain
Ansari, Mohammed Yaqoob
Ansari, Mohammed Ishaq
Malluhi, Byanne
Mohanty, Snigdha
Mishra, Subhashree
Singh, Sudhansu Sekhar
Abinahed, Julien
Al-Ansari, Abdulla
Balakrishnan, Shidin
Dakua, Sarada Prasad
Practical utility of liver segmentation methods in clinical surgeries and interventions
title Practical utility of liver segmentation methods in clinical surgeries and interventions
title_full Practical utility of liver segmentation methods in clinical surgeries and interventions
title_fullStr Practical utility of liver segmentation methods in clinical surgeries and interventions
title_full_unstemmed Practical utility of liver segmentation methods in clinical surgeries and interventions
title_short Practical utility of liver segmentation methods in clinical surgeries and interventions
title_sort practical utility of liver segmentation methods in clinical surgeries and interventions
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9128093/
https://www.ncbi.nlm.nih.gov/pubmed/35610600
http://dx.doi.org/10.1186/s12880-022-00825-2
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