The role of artificial intelligence and image processing in the diagnosis, treatment, and prognosis of liver cancer: a narrative-review

被引:3
|
作者
Dimopoulos, Platon [1 ]
Mulita, Admir [2 ,3 ]
Antzoulas, Andreas [4 ]
Bodard, Sylvain [5 ]
Leivaditis, Vasileios [6 ]
Akrida, Ioanna [4 ]
Benetatos, Nikolaos [4 ]
Katsanos, Konstantinos [1 ]
Anagnostopoulos, Christos-Nikolaos [3 ]
Mulita, Francesk [4 ]
机构
[1] Gen Univ Hosp Patras, Dept Intervent Radiol, Patras, Greece
[2] Democritus Univ Thrace, Univ Hosp Alexandroupolis, Med Phys Dept, Alexandroupolis, Greece
[3] Univ Aegean, Dept Cultural Technol & Commun, Intelligent Syst Lab, Mitilini, Greece
[4] Gen Univ Hosp Patras, Dept Surg, Patras, Greece
[5] Univ Paris Cite, Necker Hosp, Dept Radiol, Paris, France
[6] Westpfalz Klinikum, Dept Cardiothorac & Vasc Surg, Kaiserslautern, Germany
关键词
liver cancer; hepatocellular carcinoma; image processing; artificial intelligence; machine learning; medical application; HEPATOCELLULAR-CARCINOMA; RADIOFREQUENCY ABLATION; EPIDEMIOLOGY; METASTASES; SURVIVAL; RESECTION; GUIDANCE; SYSTEM; RADIOMICS; SURGERY;
D O I
10.5114/pg.2024.143147
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
Artificial intelligence (AI) and image processing are revolutionising the diagnosis and management of liver cancer. Recent advancements showcase AI's ability to analyse medical imaging data, like computed tomography scans and magnetic resonance imaging, accurately detecting and classifying liver cancer lesions for early intervention. Predictive models aid prognosis estimation and recurrence pattern identification, facilitating personalised treatment planning. Image processing techniques enhance data analysis by precise segmentation of liver structures, fusion of information from multiple modalities, and feature extraction for informed decision-making. Despite progress, challenges persist, including the need for standardised datasets and regulatory considerations.
引用
收藏
页码:221 / 230
页数:10
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