Neural Radiance Fields (NeRF), as a pioneering technique in computer vision, offer great potential to revolutionize medical imaging by synthesizing three-dimensional representations from the projected two-dimensional image data. However, they face unique challenges when applied to medical applications. This paper presents a comprehensive examination of applications of NeRFs in medical imaging, highlighting four imminent challenges, including fundamental imaging principles, inner structure requirement, object boundary definition, and color density significance. We discuss current methods on different organs and discuss related limitations. We also review several datasets and evaluation metrics and propose several promising directions for future research.

翻译：神经辐射场（NeRF）作为计算机视觉领域的先驱技术，通过从投影二维图像数据合成三维表示，为革新医学成像提供了巨大潜力。然而，当应用于医学领域时，它们面临着独特的挑战。本文全面审视了NeRF在医学成像中的应用，重点阐述了四项紧迫挑战，包括基础成像原理、内部结构需求、物体边界定义以及颜色密度重要性。我们讨论了针对不同器官的现有方法及其相关局限性。同时，我们回顾了多个数据集和评估指标，并提出了若干有前景的未来研究方向。