2025 Volume 43 Issue 5 Pages 141-147
X-ray ptychography is a technique that visualizes samples with spatial resolutions on the order of tens of nanometers by phase retrieval from diffraction intensity patterns obtained through X-ray illumination. Since imaging quality strongly depends on phase retrieval, it is essential to develop phase retrieval methods that are robust to noise and adaptable to diverse experimental conditions. In recent years, many phase retrieval approaches based on deep learning have been proposed; however, they face challenges such as the difficulty of preparing large training datasets and limited adaptability to various experimental conditions. A promising solution to these issues is the fusion of deep learning and optimization, an approach that has recently attracted considerable attention in the fields of signal processing, machine learning, and optimization. In this article, we introduce phase retrieval methods based on this hybrid approach and explain how they achieve both flexibility to changing measurement conditions and high reconstruction performance.
