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
Abstract
AbstractClinical 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.
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging
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