从面部生成合成MRI声道视图的伦理问题
Ethics of Generating Synthetic MRI Vocal Tract Views from the Face
AI总结：
该研究探讨利用Pix2PixGAN从面部运动生成伪MRI声道视图的外部-内部关联建模技术的可行性，并重点讨论了该技术涉及的隐私、同意与潜在滥用等伦理问题。
摘要：
构建能够理解口腔完整动态的口腔模型，在言语矫正、老年食品设计、牙科等研究领域至关重要。磁共振成像（MRI）技术能够捕获创建此类精细表征所需的口腔数据，是展示发音动态的有力工具。但其因成本高昂且需专业知识，实时应用受到阻碍。不断进步的生成式AI方法为解决这一障碍提供了思路，即利用多模态方法生成伪MRI视图。然而，这随即引发了关于使用可从面部观测生成MRI的技术的伦理担忧。\n本文探讨了外部-内部关联建模（E2ICM）的伦理影响。E2ICM利用面部运动推断内部结构，为MRI提供了一种经济高效的支撑技术。在这项初步研究中，我们采用Pix2PixGAN从外部发音数据生成伪MRI视图，证明了该方法的可行性。基于这一实验，我们讨论了隐私、知情同意和潜在滥用等伦理考量，这些是我们审视这一创新方法的核心内容。
英文摘要：
Forming oral models capable of understanding the complete dynamics of the oral cavity is vital across research areas such as speech correction, designing foods for the aging population, and dentistry. Magnetic resonance imaging (MRI) technologies, capable of capturing oral data essential for creating such detailed representations, offer a powerful tool for illustrating articulatory dynamics. However, its real-time application is hindered by expense and expertise requirements. Ever advancing generative AI approaches present themselves as a way to address this barrier by leveraging multi-modal approaches for generating pseudo-MRI views. Nonetheless, this immediately sparks ethical concerns regarding the utilisation of a technology with the capability to produce MRIs from facial observations. This paper explores the ethical implications of external-to-internal correlation modeling (E2ICM). E2ICM utilises facial movements to infer internal configurations and provides a cost-effective supporting technology for MRI. In this preliminary work, we employ Pix2PixGAN to generate pseudo-MRI views from external articulatory data, demonstrating the feasibility of this approach. Ethical considerations concerning privacy, consent, and potential misuse, which are fundamental to our examination of this innovative methodology, are discussed as a result of this experimentation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
