摘要
一位新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一篇报道的主题。根据NewsRx记者来自瑞士Zuary H的新闻报道，研究称，“由磁共振成像(MRI)生成的合成计算机断层成像(sCT)可以作为计划放射治疗(RT)中的CT的替代，从而消除了与多模式成像配对相关的不确定性，降低了成本和患者辐射暴露。CE/FDA批准的sCT解决方案现在可用于骨盆、大脑和头颈部。而更复杂的深度学习(DL)算法正在研究其他解剖部位。我们的新闻编辑从Zur Ich大学医院的研究中获得了一句话，“实现sC T广泛临床实施的主要挑战在于对sCT调试和质量保证（Q A）缺乏共识，导致不同医院的sCT方法存在差异。为了解决这个问题，一组专家聚集在2022年ESTRO物理研讨会上，讨论将sCT解决方案整合到诊所，并报告这一过程及其结果。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating from Zuric h, Switzerland, by NewsRx correspondents, research stated, “Synthetic computed t omography (sCT) generated from magnetic resonance imaging (MRI) can serve as a s ubstitute for planning CT in radiation therapy (RT), thereby removing registrati on uncertainties associated with multi-modality imaging pairing, reducing costs and patient radiation exposure. CE/FDA-approved sCT solutions are nowadays avail able for pelvis, brain, and head and neck, while more complex deep learning (DL) algorithms are under investigation for other anatomic sites.” Our news editors obtained a quote from the research from University Hospital Zur ich, “The main challenge in achieving a widespread clinical implementation of sC T lies in the absence of consensus on sCT commissioning and quality assurance (Q A), resulting in variation of sCT approaches across different hospitals. To addr ess this issue, a group of experts gathered at the ESTRO Physics Workshop 2022 t o discuss the integration of sCT solutions into clinics and report the process a nd its outcomes.”
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