Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI最新文献_第2页

Novel time-resolved detector for fluorescence lifetime imaging (Conference Presentation) 用于荧光寿命成像的新型时间分辨检测器(会议报告)

Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI Pub Date : 2019-03-04 DOI: 10.1117/12.2510214

C. D'Andrea, A. Farina, A. Candeo, A. D. Mora, R. Lussana, F. Villa, G. Valentini, S. Arridge

引用次数: 0

Computational improvement in single-pixel imaging contrast and resolution (Conference Presentation) 单像素成像对比度和分辨率的计算改进(会议报告)

Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI Pub Date : 2019-03-04 DOI: 10.1117/12.2506903

Robert J. Stokoe, Patrick A Stockton, A. Pezeshki, R. Bartels

引用次数: 0

Learning approach to computational microscopy 计算机显微镜的学习方法

Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI Pub Date : 2019-03-04 DOI: 10.1117/12.2515580

L. Tian, Yujia Xue, Yunzhe Li, Shiyi Cheng

{"title":"Learning approach to computational microscopy","authors":"L. Tian, Yujia Xue, Yunzhe Li, Shiyi Cheng","doi":"10.1117/12.2515580","DOIUrl":"https://doi.org/10.1117/12.2515580","url":null,"abstract":"Emerging deep learning based computational microscopy techniques promise novel imaging capabilities beyond traditional techniques. In this talk, I will discuss two microscopy applications.\u0000First, high space-bandwidth product microscopy typically requires a large number of measurements. I will present a novel physics-assisted deep learning (DL) framework for large space-bandwidth product (SBP) phase imaging,1 enabling significant reduction of the required measurements, opening up real-time applications. In this technique, we design asymmetric coded illumination patterns to encode high-resolution phase information across a wide field-of-view. We then develop a matching DL algorithm to provide large-SBP phase estimation. We demonstrate this technique on both static and dynamic biological samples, and show that it can reliably achieve 5x resolution enhancement across 4x FOVs using only five multiplexed measurements. In addition, we develop an uncertainty learning framework to provide predictive assessment to the reliability of the DL prediction. We show that the predicted uncertainty maps can be used as a surrogate to the true error. We validate the robustness of our technique by analyzing the model uncertainty. We quantify the effect of noise, model errors, incomplete training data, and “out-of-distribution” testing data by assessing the data uncertainty. We further demonstrate that the predicted credibility maps allow identifying spatially and temporally rare biological events. Our technique enables scalable DL-augmented large-SBP phase imaging with reliable predictions.\u0000Second, I will turn to the pervasive problem of imaging in scattering media. I will discuss a new deep learning- based technique that is highly generalizable and resilient to statistical variations of the scattering media.2 We develop a statistical ‘one-to-all’ deep learning technique that encapsulates a wide range of statistical variations for the model to be resilient to speckle decorrelations. Specifically, we develop a convolutional neural network (CNN) that is able to learn the statistical information contained in the speckle intensity patterns captured on a set of diffusers having the same macroscopic parameter. We then show that the trained CNN is able to generalize and make high-quality object predictions through an entirely different set of diffusers of the same class. Our work paves the way to a highly scalable deep learning approach for imaging through scattering media.","PeriodicalId":237104,"journal":{"name":"Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127346611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Single- and multi-photon shaped illumination for light-sheet fluorescence microscopy (Conference Presentation) 用于光片荧光显微镜的单光子和多光子形状照明(会议报告)

Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI Pub Date : 2019-03-04 DOI: 10.1117/12.2509353

J. Nylk, Adrià Escobet-Montalbán, Pengfei Liu, Federico Gasparoli, K. McCluskey, M. Preciado, M. Mazilu, Zhengyi Yang, F. Gunn-Moore, Sanya Aggarwal, Javier A. Tello, D. Ferrier, K. Dholakia

引用次数: 0

Towards the analytical modeling of backscattering polarimetric patterns recorded from multiply scattering systems (Conference Presentation) 对多重散射系统记录的后向散射偏振图的分析建模(会议报告)

Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI Pub Date : 2019-03-04 DOI: 10.1117/12.2509366

H. G. Akarçay, M. Hornung, Arushi Jain, M. Frenz

引用次数: 0

Controlling the depth-of-field in 3D spatial-frequency-projection fluorescence microscopy with holographic refocusing (Conference Presentation) 三维空间频率投影荧光显微镜全息重聚焦的景深控制(会议报告)

Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI Pub Date : 2019-03-04 DOI: 10.1117/12.2509842

J. Field, R. Bartels

引用次数: 0

Development of a ultrahigh speed line-scan OCT for measuring hemodynamics of chicken embryo's developing heart (Conference Presentation) 超高速线扫描OCT测量鸡胚心脏血流动力学的研究进展(会议报告)

Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI Pub Date : 2019-03-04 DOI: 10.1117/12.2510915

S. Chong, Zhen Yu Gordon Ko, Nanguang Chen

引用次数: 0

A system calibration protocol for widefield optical microscopy (Conference Presentation) 大视场光学显微镜的系统校准协议(会议报告)

Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI Pub Date : 2019-03-04 DOI: 10.1117/12.2510791

S. You, Sreevidhya Ramakrishnan, J. Chao, A. Abraham, E. Ward, R. Ober

引用次数: 0

Exploiting patterned illumination and detection in optical projection tomography (Conference Presentation) 利用光学投影断层成像中的模式照明和检测(会议报告)

Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI Pub Date : 2019-03-04 DOI: 10.1117/12.2508653

Samuel P. X. Davis, Sunil Kumar, Laura Wisniewski, Marie-Christine Ramel, L. Bugeon, T. Correia, M. Dallman, S. Arridge, P. Frankel, J. McGinty, P. French

{"title":"Exploiting patterned illumination and detection in optical projection tomography (Conference Presentation)","authors":"Samuel P. X. Davis, Sunil Kumar, Laura Wisniewski, Marie-Christine Ramel, L. Bugeon, T. Correia, M. Dallman, S. Arridge, P. Frankel, J. McGinty, P. French","doi":"10.1117/12.2508653","DOIUrl":"https://doi.org/10.1117/12.2508653","url":null,"abstract":"Optical Projection Tomography (OPT), the optical equivalent of x-ray computed tomography, reconstructs the 3D structure of a sample from a series of wide-field 2D projections acquired at different angles [1]. OPT is used to map the optical attenuation and/or fluorescence distributions of intact transparent samples without the need for mechanical sectioning. While it is typically applied to chemically cleared samples, it can also be used to image inherently transparent or weakly scattering live organisms including adult zebrafish up to ~1cm in diameter [2]. \u0000\u0000When applying OPT to live samples it is important to minimise the data acquisition time while maximising the image quality in the presence of scattering. The former issue can be addressed using compressive sensing to reduce the number of projections required [3]. Scattered light can be rejected using structured illumination [4], but this removes emission from regions the excitation modulation does not reach and reduces the available dynamic range. To address this, we have explored the rejection of scattered light by acquiring projections with parallel semi-confocal line illumination and detection in an approach we describe as slice-OPT (sl-OPT). \u0000\u0000The impact of optical scattering can also be reduced by imaging at longer wavelengths [5]. We are exploring OPT in the NIR 1&2 spectral windows. However, exotic array detectors, e.g. for short wave infrared light, are costly and so we are also developing a single pixel camera [6] approach. We will present our progress applying these techniques to 3D imaging of vasculature and tumour burden in live adult zebrafish. \u0000\u0000[1] Sharpe et al, Science, vol. 296, Issue 5567, pp. 541-545, 2002.\u0000[2] Kumar et al, Oncotarget, vol. 7, no.28, pp. 43939-43948, 2016. \u0000[3] Correia et al, PloS one, vol. 10, no. 8, p. e0136213, 2015.\u0000[4] Kristensson et al, Optics express, vol. 20, no. 13, pp. 14437-14450, 2012.\u0000[5] Shi et al., Journal of Biophotonics, vol. 9, no. 1-2, pp. 38-43, 2016.\u0000[6] Duarte et al., IEEE Signal Processing Magazine, vol. 25, no. 2, pp. 83-91, 2008.","PeriodicalId":237104,"journal":{"name":"Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124680297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Multi-layer Born scattering: an efficient model for 3D phase tomography with multiple scattering objects (Conference Presentation) 多层玻恩散射:多散射物体三维相位层析成像的有效模型(会议报告)

Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI Pub Date : 2019-03-04 DOI: 10.1117/12.2509977

Michael Chen, Hsiou-Yuan Liu, D. Ren, L. Waller

{"title":"Multi-layer Born scattering: an efficient model for 3D phase tomography with multiple scattering objects (Conference Presentation)","authors":"Michael Chen, Hsiou-Yuan Liu, D. Ren, L. Waller","doi":"10.1117/12.2509977","DOIUrl":"https://doi.org/10.1117/12.2509977","url":null,"abstract":"3D quantitative phase (refractive index) microscopy reveals volumetric structure of biological specimens. Optical diffraction tomography (ODT) is a common technique for 3D phase imaging. By angularly scanning a spatially coherent light source and measuring scattered fields on the imaging plane, 3D refractive index (RI) is recovered by solving an inverse problem. However, ODT often linearizes the process by using a weakly scattering model, e.g. the first Born approximation or Rytov approximation, which underestimate the RI and fail to reconstruct realistic shape of high RI contrast multiple scattering objects. On the other hand, non-linear models such as the multi-slice or beam propagation methods mitigate artifacts by modeling multiple scattering. However, they ignore back-scattering and intra-slice scattering and make a paraxial approximation by assuming each slice is infinitesimally thin. In this work, we propose a new 3D scattering model Multi-layer Born (MLB), which treats the object as thin 3D slabs with finite thickness and applies the first Born approximation on each slab as the field propagates through the object, increasing the accuracy significantly. In the meantime, a similar computation complexity is achieved comparing to the previously proposed multi-slice models. Therefore, MLB can achieve accuracy similar to that of FDTD or SEAGLE, a frequency domain solver, with orders of magnitude less computation time. In addition to forward scattering, multiple back-scattering effects are also captured by MLB unlike existing models. We apply MLB to recover the RI distribution of 3D phantoms and biological samples with intensity-only measurements from an LED array microscope and show that the results are superior to existing methods.","PeriodicalId":237104,"journal":{"name":"Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130680294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1