神经肿瘤成像中的人工智能:临床应用案例和未来展望的简要回顾

Ji Eun Park
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引用次数: 2

摘要

人工智能(AI)技术,包括端到端的深度学习方法和带有机器学习的放射组学,已经被开发用于神经肿瘤学中基于成像的各种任务。在这篇简短的综述中,总结了人工智能在神经肿瘤学成像中的应用案例:图像质量改善、转移检测、放射基因组学和治疗反应监测。然后,我们简要概述了生成对抗性网络,以及合成图像在基于图像的任务和图像翻译任务的各种深度学习算法中作为新数据输入的潜在效用。最后,我们强调了队列和临床试验作为人工智能在神经肿瘤学成像中临床应用的真正验证的重要性。
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Artificial Intelligence in Neuro-Oncologic Imaging: A Brief Review for Clinical Use Cases and Future Perspectives
The artificial intelligence (AI) techniques, both deep learning end-to-end approaches and radiomics with machine learning, have been developed for various imaging-based tasks in neuro-oncology. In this brief review, use cases of AI in neuro-oncologic imaging are summarized: image quality improvement, metastasis detection, radiogenomics, and treatment response monitoring. We then give a brief overview of generative adversarial network and potential utility of synthetic images for various deep learning algorithms of imaging-based tasks and image translation tasks as becoming new data input. Lastly, we highlight the importance of cohorts and clinical trial as a true validation for clinical utility of AI in neuro-oncologic imaging.
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