Dimopoulos Platon, Mulita Admir, Antzoulas Andreas, Bodard Sylvain, Leivaditis Vasileios, Akrida Ioanna, Benetatos Nikolaos, Katsanos Konstantinos, Anagnostopoulos Christos-Nikolaos, Mulita Francesk
Department of Interventional Radiology, General University Hospital of Patras, Patras, Greece.
Medical Physics Department, Democritus University of Thrace, University Hospital of Alexandroupolis, Alexandroupolis, Greece.
Prz Gastroenterol. 2024;19(3):221-230. doi: 10.5114/pg.2024.143147. Epub 2024 Sep 18.
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.
人工智能(AI)和图像处理正在彻底改变肝癌的诊断和管理。最近的进展展示了人工智能分析医学影像数据的能力,如计算机断层扫描和磁共振成像,能够准确检测和分类肝癌病变以便早期干预。预测模型有助于预后评估和复发模式识别,促进个性化治疗方案的制定。图像处理技术通过对肝脏结构进行精确分割、融合来自多种模态的信息以及提取特征以进行明智决策,从而增强了数据分析。尽管取得了进展,但挑战依然存在,包括对标准化数据集的需求和监管方面的考虑。