Artificial intelligence (AI) is revolutionizing cancer imaging, enhancing screening, diagnosis, and treatment options for clinicians. AI-driven applications, particularly deep learning and machine learning, excel in risk assessment, tumor detection, classification, and predictive treatment prognosis. Machine learning algorithms, especially deep learning frameworks, improve lesion characterization and automated segmentation, leading to enhanced radiomic feature extraction and delineation. Radiomics, which quantifies imaging features, offers personalized treatment response predictions across various imaging modalities. AI models also facilitate technological improvements in non-diagnostic tasks, such as image optimization and automated medical reporting. Despite advancements, challenges persist in integrating AI into healthcare, tracking accurate data, and ensuring patient privacy. Validation through clinician input and multi-institutional studies is essential for patient safety and model generalizability. This requires support from radiologists worldwide and consideration of complex regulatory processes. Future directions include elaborating on existing optimizations, integrating advanced AI techniques, improving patient-centric medicine, and expanding healthcare accessibility. AI can enhance cancer imaging, optimizing precision medicine and improving patient outcomes. Ongoing multidisciplinary collaboration between radiologists, oncologists, software developers, and regulatory bodies is crucial for AI’s growing role in clinical oncology. This review aims to provide an overview of the applications of AI in oncologic imaging while also discussing their limitations.
人工智能（AI）正在革新癌症影像学，为临床医生提升筛查、诊断和治疗选择。AI驱动的应用，特别是深度学习和机器学习，在风险评估、肿瘤检测、分类及治疗预后预测方面表现卓越。机器学习算法，尤其是深度学习框架，改善了病灶特征描述与自动分割，从而提升了影像组学特征提取与病灶勾画的精度。影像组学通过量化影像特征，为多种影像模态提供个性化的治疗反应预测。AI模型还在非诊断任务中推动技术进步，如图像优化和自动化医疗报告生成。尽管取得进展，将AI整合到医疗保健中仍面临挑战，包括追踪准确数据与保障患者隐私。通过临床医生参与和多机构研究进行验证，对患者安全和模型泛化能力至关重要。这需要全球放射科医生的支持，并考虑复杂的监管流程。未来方向包括深化现有优化、整合先进AI技术、改善以患者为中心的医疗模式，并扩大医疗可及性。AI能够增强癌症影像学，优化精准医疗并改善患者预后。放射科医生、肿瘤学家、软件开发者和监管机构之间持续的多学科合作，对于AI在临床肿瘤学中日益增长的作用至关重要。本综述旨在概述AI在肿瘤影像学中的应用，同时探讨其局限性。
Evolving and Novel Applications of Artificial Intelligence in Cancer Imaging
肿瘤(癌症)患者之家