AI 中文总结
该研究将点扩散函数工程视为相位检索问题，提出神经场光瞳设计方法，可优化任意用户定义的三维PSF分布，为三维PSF工程提供灵活且对初始化鲁棒的框架。
AI 中文摘要
通过光瞳平面调制实现的点扩散函数（PSF）工程是显微成像中用于获得特定成像特性的技术，例如深度编码或扩展景深。现有PSF设计方法通常依赖大量领域知识和特定任务的基函数，难以在不同应用间通用。我们将PSF工程任务视为相位检索问题，提出一种神经场光瞳设计方法，可针对任意用户定义的三维PSF分布优化相位轮廓。该方法为各类应用的三维PSF工程提供了灵活框架，其隐式正则化相比逐像素优化方法对初始化更具鲁棒性。
英文摘要
Point spread function (PSF) engineering through pupil plane modulation is a technique used in microscopy to achieve specific imaging properties, such as depth encoding or extended depth of field. Existing PSF design methods often rely on extensive domain knowledge and task-specific basis functions, making it difficult to generalize across different applications. We treat the PSF engineering task as a phase retrieval problem and propose a neural field pupil design method that optimizes a phase profile for any arbitrary, user-defined 3D PSF distribution. This provides a flexible framework for 3D PSF engineering for various applications with implicit regularization that proves robust to initialization compared to pixel-wise optimization methods
