CIF: Small: Sequential and Compound Estimation for Computational Imaging Systems

CIF：小型：计算成像系统的顺序和复合估计

• 批准号: 1815896
• 负责人: Vivek Goyal
• 金额: $ 49.05万
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1815896&HistoricalAwards=false
• 关键词: CIF; Small; Sequential; Compound; Estimation

The widespread use of imaging technologies across biology, chemistry, material science, medicine, and other fields is motivated by the great innate human ability for visual information processing. Imaging is often limited, however, by the damage to a sample caused by the imaging process, such as sputtering due to the incident ion or electron beam in scanned beam microscopy. With conventional methods, a sample may be destroyed before enough information has been gained to form a useful image. This project develops methods for reducing the necessary dose in microscopy systems. This may make it possible to image molecular or biological species not before imaged, or to increase the speed of imaging so that new dynamic phenomena are revealed. The project also includes dissemination of results to broad audiences through expository writing, general-audience talks, cross-disciplinary training, and production of teaching materials. Poisson models are often exploited when measured signals are due to small numbers of detected particles. A major premise of this project is to combine the Poisson modeling of such detection counts with Poisson modeling of the numbers of interacting particles in low-current beams. The project develops theory and methods for the resulting compound estimation problems. The project explores the use of time-resolved sensing to reduce the uncertainty due to the source shot noise in compound processes. Furthermore, time-resolved sensing enables the decomposition of a data collection process into a sequence of less-damaging steps, and the project will develop theory and methods for sequential estimation and adaptive data collection. Analysis will inspire and be informed by proof-of-concept experiments. The ultimate limit of learning about a sample without damaging it is achieved with certain quantum-mechanical interaction-free measurements. The project will develop theory for sequential interaction-free measurements to establish when they may be superior to conventional measurements.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.

成像技术在生物学、化学、材料科学、医学和其他领域的广泛应用是由人类天生的视觉信息处理能力所驱动的。然而，成像通常受到成像过程对样品造成的损害的限制，例如扫描束显微镜中由于入射离子或电子束而产生的溅射。用传统的方法，样本可能在获得足够的信息形成有用的图像之前就被破坏了。本项目开发减少显微镜系统中必要剂量的方法。这可能使之前未成像的分子或生物物种成像成为可能，或者提高成像速度，从而揭示新的动态现象。该项目还包括通过说明文、普通听众讲座、跨学科培训和编写教材向广大听众传播成果。当测量到的信号是由少量被探测到的粒子引起时，通常利用泊松模型。该项目的一个主要前提是将这种检测计数的泊松模型与低电流光束中相互作用粒子数的泊松模型结合起来。该项目为由此产生的复合估计问题发展了理论和方法。该项目探索使用时间分辨传感来减少复合过程中由于源射击噪声而产生的不确定性。此外，时间分辨传感能够将数据收集过程分解为一系列破坏性较小的步骤，该项目将开发用于顺序估计和自适应数据收集的理论和方法。分析将受到概念验证实验的启发和启发。在不破坏样品的情况下了解样品的最终极限是通过某些量子力学无相互作用的测量来实现的。该项目将为顺序无相互作用测量发展理论，以确定它们何时可能优于传统测量。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Continuous-Time Modeling and Analysis of Particle Beam Metrology

• DOI: 10.1109/jsait.2023.3283911
• 发表时间: 2023-03
• 期刊: IEEE Journal on Selected Areas in Information Theory
• 作者: A. Agarwal;Minxu Peng;V. Goyal

Beyond Binomial and Negative Binomial: Adaptation in Bernoulli Parameter Estimation

• DOI: 10.1109/tci.2019.2913108
• 发表时间: 2018-09
• 期刊: IEEE Transactions on Computational Imaging
• 影响因子: 5.4
• 作者: Safa C. Medin;John Murray-Bruce;D. Castañón;Vivek K Goyal

Denoising Particle Beam Micrographs With Plug-and-Play Methods

• DOI: 10.1109/tci.2023.3282042
• 发表时间: 2022-08
• 期刊: IEEE Transactions on Computational Imaging
• 影响因子: 5.4
• 作者: Minxu Peng;Ruangrawee Kitichotkul;Sheila W. Seidel;Christopher C. Yu;V. Goyal

Offline Secondary Electron Counting and Conditional Re-illumination in SEM

SEM 中的离线二次电子计数和条件重照明

• DOI: 10.1017/s1431927620017249
• 发表时间: 2020
• 期刊: Microscopy and Microanalysis
• 影响因子: 2.8
• 作者: Agarwal, Akshay;Simonaitis, John;Goyal, Vivek;Berggren, Karl
• 通讯作者: Berggren, Karl

Online Beam Current Estimation in Particle Beam Microscopy

• DOI: 10.1109/tci.2022.3182212
• 发表时间: 2021-11
• 期刊: IEEE Transactions on Computational Imaging
• 影响因子: 5.4
• 作者: Sheila W. Seidel;Luisa Watkins;Minxu Peng;A. Agarwal;Christopher C. Yu;V. Goyal