人工智能在神经影像学中的临床应用

K. Choi, L. Sunwoo
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引用次数: 11

摘要

以深度学习(DL)为动力的人工智能(AI)在图像识别任务方面取得了显著进展。在过去的十年里,人工智能已经证明了它在医学成像领域应用的可行性。在人工智能的帮助下,神经影像学临床实践的各个方面都可以得到改善。例如,人工智能可以帮助检测脑转移,预测脑肿瘤的治疗反应,生成动态对比增强MRI的参数图,并通过从输入图像中提取显著特征来加强放射组学研究。此外,可以通过基于人工智能的图像重建或运动伪影减少来提高图像质量。在这篇综述中,我们总结了近年来DL在神经影像学各个方面的临床应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence in Neuroimaging: Clinical Applications
Review Article Artificial intelligence (AI) powered by deep learning (DL) has shown remarkable progress in image recognition tasks. Over the past decade, AI has proven its feasibility for applications in medical imaging. Various aspects of clinical practice in neuroimaging can be improved with the help of AI. For example, AI can aid in detecting brain metastases, predicting treatment response of brain tumors, generating a parametric map of dynamic contrast-enhanced MRI, and enhancing radiomics research by extracting salient features from input images. In addition, image quality can be improved via AI-based image reconstruction or motion artifact reduction. In this review, we summarize recent clinical applications of DL in various aspects of neuroimaging.
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