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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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Detalles Bibliográficos
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
Descripción
Sumario: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.