人工智能在肝细胞癌放射诊断中的应用进展

Wasim Awal, J. D. Groot, J. Chan
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引用次数: 0

摘要

肝细胞癌(HCC)是全球癌症相关死亡的第三大常见原因。与大多数其他癌症不同,HCC可以仅通过影像学对高危患者进行诊断。然而,这往往是复杂的非典型或不确定的特征,需要活检或密切随访与系列成像。人工智能(AI)有可能实现更准确的肿瘤分类,从而避免不必要的活组织检查。此外,早期诊断开辟了治愈治疗的潜力,并改善了患者的预后。许多人工智能模型,包括机器学习、卷积神经网络和基于放射学的模型,已经在肝脏病变的超声、CT和MRI图像上进行了测试。下面的评论将概述这一领域最具影响力的论文。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advances in Artificial Intelligence for the Radiological Diagnosis of Hepatocellular Carcinoma
Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths globally. Unlike most other cancers, HCC can be diagnosed solely on imaging for high-risk patients. However, this is frequently complicated by atypical or indeterminate features necessitating biopsy or close follow-up with serial imaging. Artificial intelligence (AI) has the potential to allow for more accurate tumour classification and, thus, avoid unnecessary biopsies. Additionally, earlier diagnosis opens up the potential for curative therapies and improves patient outcomes. A number of artificial intelligence models, including machine learning, convolutional neural networks and radiomics-based models have been tested on ultrasound, CT and MRI images of liver lesions. The following review will outline the most impactful papers in this field.
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