Collaborative Research: Computational Ptychography: Fast Algorithms, Recovery Guarantees, and Applications to Bio-Imaging

合作研究：计算叠印术：快速算法、恢复保证以及在生物成像中的应用

• 批准号: 2012140
• 负责人: Guoan Zheng
• 金额: $ 14.25万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2012140&HistoricalAwards=false
• 关键词: Collaborative; Research; Computational; Ptychography; Fast

Ptychography refers to an imaging technique where overlapping regions of an object are illuminated, usually by placing a pinhole (and possibly a mask) between a light source and the object, and sequentially moving the pinhole. The resulting diffraction patterns are then sampled and used to calculate an approximate image of the object. The underlying physics of this imaging process dictates that one can only directly collect the intensity of the diffraction patterns, and not the critically important phase information. This makes the recovery of an accurate image extremely challenging. Nevertheless, through careful application of heuristic algorithms, practitioners have successfully employed these methods in a vast array of important applications such as the study of drug delivery mechanisms in complex bio-molecules, study of solar cells and battery chemistry, and the study of fracture dynamics in materials science. Despite these impressive results, several challenges remain, including the need to image larger and larger specimens at increasingly higher resolutions, and the growing size of datasets generated by a new generation of advanced imaging apparatus. This project seeks to develop fast, highly efficient, noise-robust, and mathematically rigorous computational methods in support of this next generation of high-throughput, high-resolution ptychographic imaging. The broader impacts of this project include curriculum development and training of students, including those from underrepresented groups, application of the computational methods to bio-imaging applications in the lab, and knowledge dissemination to raise the scientific literacy of the public.Mathematically, much progress has been recently made in understanding ptychographic imaging and in analyzing novel algorithms for signal recovery from phase-less measurements. However, these algorithms and their attendant analysis often assume one collects the modulus of generalized linear measurements, where the discretized measurements are highly random. In line with applications, a focus of this project is on designing practical measurement schemes of the type actually used in ptychographic imaging. Another major difficulty in realistic phase-less imaging applications is that the imaging system's measurement masks/probes can often only be approximately implemented and partially known. Hence, another major objective of this project is the development of novel theoretical and algorithmic results for the blind ptychography problem. In either case, the emphasis is on constructing provably accurate recovery algorithms that are fast enough to scale to large problems in multiple dimensions. These tasks require developing and using a broad range of mathematical tools. Techniques from time-frequency analysis, frame theory, spectral graph theory, high-dimensional probability, and compressive sensing will be necessary for analyzing the measurement schemes and for providing rigorous theoretical guarantees for the developed recovery algorithms. Finally, a key component of this project is the application of these computational methods to real ptychographic phase-less imaging setups and bio-imaging applications. More specifically, a novel wide-field, high-resolution lense-less on-chip microscopy platform will be designed, which puts the theoretical techniques developed as part of this project into practice.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

叠层照相术是指一种成像技术，其中物体的重叠区域被照亮，通常通过在光源和物体之间放置一个针孔（也可能是一个掩模），并顺序移动该针孔。然后对所得衍射图案进行采样并用于计算物体的近似图像。这一成像过程的基本物理原理决定了人们只能直接收集衍射图案的强度，而不能收集至关重要的相位信息。这使得恢复准确的图像变得极具挑战性。尽管如此，通过仔细应用启发式算法，从业者已经成功地将这些方法应用于大量重要应用，例如复杂生物分子中药物输送机制的研究、太阳能电池和电池化学的研究以及断裂动力学的研究在材料科学中。尽管取得了这些令人印象深刻的结果，但仍然存在一些挑战，包括需要以越来越高的分辨率对越来越大的标本进行成像，以及新一代先进成像设备生成的数据集规模不断扩大。该项目旨在开发快速、高效、抗噪声且数学上严格的计算方法，以支持下一代高通量、高分辨率叠层成像。该项目更广泛的影响包括课程开发和学生培训（包括来自代表性不足群体的学生）、计算方法在实验室生物成像应用中的应用以及知识传播以提高公众的科学素养。在数学方面，取得了很大进展最近在理解叠层成像和分析从无相测量中恢复信号的新算法方面取得了进展。然而，这些算法及其伴随的分析通常假设收集广义线性测量的模数，其中离散测量是高度随机的。根据应用，该项目的重点是设计叠层成像中实际使用的类型的实用测量方案。现实无相成像应用中的另一个主要困难是成像系统的测量掩模/探针通常只能近似实现并且部分已知。因此，该项目的另一个主要目标是为盲叠印问题开发新颖的理论和算法结果。无论哪种情况，重点都是构建可证明准确的恢复算法，该算法足够快，可以扩展到多个维度的大型问题。这些任务需要开发和使用广泛的数学工具。时频分析、框架理论、谱图理论、高维概率和压缩感知等技术对于分析测量方案和为开发的恢复算法提供严格的理论保证是必要的。最后，该项目的一个关键组成部分是将这些计算方法应用于真实的叠层无相成像设置和生物成像应用。更具体地说，将设计一种新颖的宽视场、高分辨率无透镜片上显微镜平台，将作为该项目一部分开发的理论技术付诸实践。该奖项反映了 NSF 的法定使命，并被认为是值得的通过使用基金会的智力优势和更广泛的影响审查标准进行评估来提供支持。

项目成果

Ptychographic sensor for large-scale lensless microbial monitoring with high spatiotemporal resolution

用于高时空分辨率的大规模无透镜微生物监测的叠层记录传感器

• DOI: 10.1016/j.bios.2021.113699
• 发表时间: 2022-01
• 期刊: Biosensors and Bioelectronics
• 影响因子: 12.6
• 作者: Jiang, Shaowei;Guo, Chengfei;Bian, Zichao;Wang, Ruihai;Zhu, Jiakai;Song, Pengming;Hu, Patrick;Hu, Derek;Zhang, Zibang;Hoshino, Kazunori;et al
• 通讯作者: et al

Remote referencing strategy for high-resolution coded ptychographic imaging

高分辨率编码叠层成像的远程参考策略

• DOI: 10.1364/ol.481395
• 发表时间: 2023-01
• 期刊: Optics Letters
• 影响因子: 3.6
• 作者: Wang, Tianbo;Song, Pengming;Jiang, Shaowei;Wang, Ruihai;Yang, Liming;Guo, Chengfei;Zhang, Zibang;Zheng, Guoan
• 通讯作者: Zheng, Guoan

Freeform Illuminator for Computational Microscopy

用于计算显微镜的自由形状照明器

• DOI: 10.34133/icomputing.0015
• 发表时间: 2023-01
• 期刊: Intelligent Computing
• 作者: Song, Pengming;Wang, Tianbo;Jiang, Shaowei;Guo, Chengfei;Wang, Ruihai;Yang, Liming;Zhou, You;Zheng, Guoan
• 通讯作者: Zheng, Guoan

Optical ptychography for biomedical imaging: recent progress and future directions [Invited]

用于生物医学成像的光学叠层成像：最新进展和未来方向 [邀请]

• DOI: 10.1364/boe.480685
• 发表时间: 2023-01
• 期刊: Biomedical Optics Express
• 影响因子: 3.4
• 作者: Wang, Tianbo;Jiang, Shaowei;Song, Pengming;Wang, Ruihai;Yang, Liming;Zhang, Terrance;Zheng, Guoan
• 通讯作者: Zheng, Guoan

High-throughput lensless whole slide imaging via continuous height-varying modulation of a tilted sensor

通过倾斜传感器的连续高度变化调制进行高通量无透镜全玻片成像

• DOI: 10.1364/ol.437832
• 发表时间: 2021-10
• 期刊: Optics Letters
• 影响因子: 3.6
• 作者: Jiang, Shaowei;Guo, Chengfei;Hu, Patrick;Hu, Derek;Song, Pengming;Wang, Tianbo;Bian, Zichao;Zhang, Zibang;Zheng, Guoan
• 通讯作者: Zheng, Guoan