X射线同轴全息成像中超越均匀物体假设的相位恢复
Phase retrieval beyond the homogeneous object assumption for X-ray in-line holographic imaging
AI总结：
针对X射线近场全息中均匀物体假设的局限，提出一种推广CTF方法的高效相位恢复算法，并通过实验证明其在相近计算成本下获得更优重建质量。
摘要：
X射线近场全息已被证明是一种强大的二维和三维成像技术，其应用范围从生物医学研究到材料科学。然而，为了从测量强度中重建有意义的定量图像，该技术依赖于计算相位恢复，而在许多情况下，相位恢复假设样品的相移和衰减系数成比例。在此，我们展示了一种不依赖于这种均匀物体假设的高效相位恢复算法，它是成熟的对比度传递函数（CTF）方法的推广。随后，我们研究了其稳定性，并给出了一项实验研究，将所提出的算法与既有方法进行比较。在相近的计算成本下，该算法相比成熟的基于CTF的方法表现出更优的重建质量。我们的分析增进了对均匀物体假设的基础性理解，并且所提出的算法将有助于提升生物医学应用中近场全息的图像质量。
英文摘要：
X-ray near field holography has proven to be a powerful 2D and 3D imaging technique with applications ranging from biomedical research to material sciences. To reconstruct meaningful and quantitative images from the measurement intensities, however, it relies on computational phase retrieval which in many cases assumes the phase-shift and attenuation coefficient of the sample to be proportional. Here, we demonstrate an efficient phase retrieval algorithm that does not rely on this homogeneous-object assumption and is a generalization of the well-established contrast-transfer-function (CTF) approach. We then investigate its stability and present an experimental study comparing the proposed algorithm with established methods. The algorithm shows superior reconstruction quality compared to the established CTF-based method at similar computational cost. Our analysis provides a deeper fundamental understanding of the homogeneous object assumption and the proposed algorithm will help improve the image quality for near-field holography in biomedical applications
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