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CIF: Small: Collaborative Research: Signal Processing for Nonlinear Diffractive Imaging: Acquisition, Reconstruction, and Applications

CIF：小型：协作研究：非线性衍射成像的信号处理：采集、重建和应用

基本信息

批准号：
1813848
负责人：
Lei Tian
金额：
$ 25.07万
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 2021-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1813848&HistoricalAwards=false
关键词：
CIF Small Collaborative Research Signal

项目摘要

There is a growing need in biomedical research to observe biological structure and processes on the length scales smaller than 100nm. Conventional optical systems cannot effectively provide such information, however, due to the infamous diffraction limit. The formulation of the diffraction limit fundamentally relies on the presumed linearity in the interaction between the illuminating light and the object. The goal of this project is to overcome the diffraction limit by exploiting nonlinearities from a modern signal processing perspective. This project will lay out theoretical, algorithmic, and instrumentation foundation for nonlinear diffractive imaging. The outcome of this project can open up many possibilities of high-resolution imaging in highly scattering media that are ubiquitous in science and medicine, including histology, cytometry, brain mapping, and drug discovery. The proposed activities will also promote education through the training of students in a wide range of topics within signal processing, computational imaging, and optics, and through related curriculum development efforts where the basic themes of the proposed research will be incorporated in courses taught by the investigators.The focus of this research is to develop computational imaging methods that fully harness the information encoded in two types of nonlinearities: object-light interactions and prior assumptions on the objects. Concretely, the work will focus on: (a) efficient schemes for data acquisition, (b) scalable algorithms for 3D reconstruction, and (c) two novel application platforms for validation. Results from this research will lead to a single, holistic signal processing framework that can maximally extract the information encoded in nonlinear 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.

在生物医学研究中，越来越需要在小于100 nm的长度尺度上观察生物结构和过程。然而，由于臭名昭著的衍射极限，传统的光学系统不能有效地提供这样的信息。衍射极限的公式基本上依赖于照明光和物体之间相互作用的假定线性。该项目的目标是从现代信号处理的角度，通过利用非线性来克服衍射极限。本计画将为非线性绕射成像之理论、演算法及量测奠定基础。该项目的成果可以在科学和医学中普遍存在的高散射介质中开辟许多高分辨率成像的可能性，包括组织学，细胞计数，脑成像和药物发现。拟议的活动还将通过对学生进行信号处理、计算成像和光学等广泛专题的培训来促进教育，并通过相关的课程开发工作，将拟议研究的基本主题纳入调查人员教授的课程中。这项研究的重点是开发计算成像方法，充分利用两种类型的编码信息，非线性：物体-光的相互作用和对物体的先验假设。具体而言，工作将集中在：（a）有效的数据采集方案，（B）可扩展的三维重建算法，和（c）两个新的应用平台进行验证。这项研究的结果将导致一个单一的，整体的信号处理框架，可以最大限度地提取非线性测量中编码的信息。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。