Surgical Research, Hamad Medical Corporation, Doha, Qatar.
McGill University, Montreal, Canada.
BMC Med Imaging. 2022 May 24;22(1):97. doi: 10.1186/s12880-022-00825-2.
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.
临床影像(例如磁共振成像和计算机断层扫描)是临床医生的重要辅助手段,有助于疾病的诊断和适当干预措施的规划。在肝癌(HCC)等恶性疾病中更是如此,临床医生通过影像分割(例如肝脏和肿瘤的准确勾画)来优化诊断、分期和治疗计划以及干预措施(例如移植、手术切除、放疗、PVE、栓塞等)。因此,分割方法可能会对诊断和治疗结果产生影响。本文全面回顾了 2012 年至 2021 年相关的分割方法文献,并根据其在 HCC 中的临床应用(即手术和放射学干预)进行了广泛分类。分类基于精度、准确性和自动化等参数。