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【搜狐新闻】片上无透镜全息显微技术  —— 让“显微镜”抛弃“显微物镜”

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发表时间:2022-06-09 17:46来源:搜狐新闻网址:https://www.sohu.com/a/561351241_121406440

1.显微成像应用与挑战


在我们的世界里,没有一种物质的形式会比活细胞更令人惊讶:微小、脆弱、复杂得不可思议。然而细胞非常微小,直到17世纪,列文虎克发明光学显微镜,人类才第一次观测到细胞(如图1所示)。在过去的几个世纪中,显微镜已逐步演变成一种极为重要且精密的观察与计量科学仪器,涵盖了从微小细菌到组织切片的可视化观察,为人类探索微观世界做出了重要贡献。


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图1 列文虎克发明第一台显微镜


近年来,随着生活水平的提高,人们对生活质量和身体健康的关注度越来越高。然而,各类疾病年轻化态势已成为不争的事实。疾病的早期发现、精确诊断是进行有效治疗的关键。作为生物医学检测、分析的核心仪器——光学显微镜,在早期筛查、细胞培养、药物研发等过程中发挥着举足轻重的作用。

随着生命科学问题的深入研究,检验医学对检测手段需求的提高,光学显微成像技术获得了突飞猛进的发展,产生了一系列新的光学显微镜,如相衬显微镜[1]、微分干涉相衬显微镜[2]、荧光显微镜[3]–[5]、激光共聚焦显微镜[6], [7]。这些显微镜与传统的明场显微镜对比,可以获得更高的成像分辨率和成像质量,为疾病诊断尤其是重大恶性疾病的早期诊断提供影像学依据(如图2所示)

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图2 光学显微镜在生物医学检测领域方面的应用

然而,伴随着显微镜功能的增加、性能的提升,显微系统愈加笨重、复杂、难以维护以及日趋昂贵。此外,利用荧光显微镜或者激光共聚焦显微镜对生物样本进行观察时,往往需要先对待观察样本进行化学染色或荧光标记,以提高成像衬度[8]。这一过程又对待测样本的制备流程提出了更高要求。这两方面限制了将其进一步应用于具有无损化、高分辨、大视场、智能化需求的应用领域,使其通常情况下仅存于基础设施条件较好、具有专业技术人员的实验室或医疗机构(如图3所示)

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图3 现代精密显微镜的局限


但与现实情况相矛盾的是,很多流行性疾病多发于基础医疗水平低下的地区。这些地区更需要性能优良的显微镜来帮助鉴别病原体。因此,在保证光学显微设备成像质量的前提下,更小的体积、更低的成本、更简便的操作,将可以急剧地降低医疗研究以及检测的门槛,为资源条件有限地区的急、重症病人提供更快捷、更低价的即时诊断(Point-of-Care Testing,POCT)与治疗。


2.应运而生 无透镜显微镜


“计算光学显微成像”[9]是近十年来兴起的一项技术。不同于传统光学显微成像“所见即所得”的成像方式[10],计算光学显微成像采用“先调制,再拍摄,最后解调”的成像方式。它可与显微镜、全息术和光散射技术相结合,实现对形态与动态的纳米级分辨率,二维、三维、四维(即时间分辨断层成像)完全透明结构的非破坏性成像。相比于传统光学显微成像,计算光学显微成像展现了革命性的优势:成像质量更高,成像系统结构更简单,突破光学系统与图像采集设备的物理限制等,使其在信息获取能力、功能、性能指标等方面获得显著提升。


近年来,发光二极管(LED)与图像传感器等光电器件、现代数字计算机和智能手机的快速革新为计算光学显微镜的快速发展提供了新的机遇与空间。其中,“片上无透镜显微成像技术”因其体积小型化、成本低廉化等特点成为极具应用前景的研究领域。无透镜片上显微成像技术[11]是一种无需借助任何透镜,直接将待测物体置于或者将其紧靠传感器表面进行成像的高通量显微成像技术。“无透镜”(lens-free),即不采用传统光学透镜对样品进行成像(如图4所示)。无透镜设计可降低系统成本、简化设备结构,并避免成像视场与成像分辨率之间的矛盾。


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4 无透镜显微镜的优势


无透镜片上显微成像技术主要分为三类,即接触式投影成像技术[12]–[18]、基于衍射的无透镜显微成像技术[19]–[33]和深度学习技术[34]–[37](如图5所示)。投影式成像中,样品直接放置于传感器表面,空间相干性有限的光源直接照射相位物体,样品的投影直接由图像传感器采集。这种方法无需任何重构方法,不仅可以用于静态物体的成像还可以用于细胞分裂、运动以及其他特性的监测。


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图5 无透镜显微镜分类


然而,此类方法要求距离传感器非常近(需要去除传感器保护玻璃),这将导致传感器非常容易损坏。后一类无透镜显微成像技术本质上是依赖计算来消除或者部分消除样品和成像面之间的产生的衍射现象。具体地,在重构物体的聚焦图像时,由于缺少相位信息,所以重构后的聚焦图像往往存在着共轭像,因此相位恢复是无透镜全息显微成像过程中的关键因素之一。

由于样品—传感器距离较小,成像系统数值孔径接近于1,导致成像分辨率受到传感器像素大小的限制。因此,提升成像分辨率成为无透镜片上显微成像技术必须克服的难题[38]。为实现像素超分辨成像,发展了诸如光源/样品/传感器横向位移(光源阵列)等方法以获得高分辨率全息图,用于恢复同轴成像中丢失的相位信息(相位恢复)。这通常需要多幅全息图,例如,多个样品到传感器的距离[24], [39]–[43]、照明角度[44],[45]、照明波长[46], [47](如图6所示)。每一幅全息图都可作为光场振幅的物理约束,从而在迭代算法中可以强制使得计算的复振幅场与这些采集值保持一致。

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图6 无透镜显微成像难题及克服方法


上述像素超分辨率技术结合相位恢复算法,可使无透镜显微镜获得亿像素级高通量成像。通常,上述超分辨技术需要借助额外的可控机械装置或波长校准和色散补偿过程来获取所需的系列低分辨率图像,再通过特定的计算过程获得更小的有效像素,从而达到超分辨成像的效果。但机械装置的引入,将导致整个系统的复杂性与成本显著增加,是一个需要协调平衡的重要因素。

3.无透镜全息显微镜CyteLive 高通量细胞分析仪

这里介绍本实验室设计的无透镜显微镜设备:无透镜全息显微镜CyteLive —— 高通量细胞分析仪。无透镜全息显微镜CyteLive结构简单,它去除了传统显微系统中的物镜,采用多波长LED阵列照明模式,利用紧贴待测样品的成像探测器直接记录近场衍射图像。无透镜全息显微镜CyteLive基于菲涅尔域中光强传输与波长的可置换性,使用多波长照明实现非机械离焦,并利用非干涉相位恢复技术(光强传输方程,TIE)[48]–[51]实现高通量重构样本信息。

因此,无透镜全息显微镜CyteLive可在29.8474 mm2的宽视场下,实现870 nm的超像素分辨率成像,为生物医学等领域提供对样品进行无标记、高通量定量相位成像,有望为远程医疗应用或医疗点诊断提供具有成本效益的显微工具(如图7所示)。

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图7 设计概念、成像功能、性能指标和预期的生物医学应用


1) 系统结构

无透镜全息显微镜CyteLive不包含任何可移动结构,主要由彩色LED单元和单色CMOS传感器组成,如图8所示。

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图8 系统示意图


LED照明可产生近似空间相干照明,其中心波长分别为631 nm(红色)、522 nm(绿色)和465 nm(蓝色)(带宽 ~10 nm,尺寸 ~100 μm),不仅有效抑制了由寄生反射引起的散斑噪声与失真,还极大降低了无透镜显微镜的硬件成本。LED放置在距离样品平面 80 mm处,依次产生红光、绿光和蓝光来照亮样品。使用像素尺寸为1.67 µm的工业相机(The Imaging Source,DMK-24UJ003,3872×2764)拍摄图像。空间相干门控样品需尽可能靠近传感器表面放置(< 1 mm),以便于高分辨率相位成像。基于上述配置下,无透镜全息显微镜CyteLive尺寸为130×80×75 mm3。


2) 原理算法

无透镜全息显微镜CyteLive通过波长扫描,来捕获不同波长(红、绿、蓝)下的三个强度图像。基于衍射传播理论,波长和传播距离总是成对出现,这意味着波长的变化对光场传播的影响与传播距离的变化是等效的。因此,在多波长照明下捕获的图像可以转换为多深度图像,如图9所示,使用TIE相位恢复算法和GS迭代算法实现像素超分辨的重建[52]。

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图9 无透镜全息显微镜CyteLive技术路线图


为避免算法在早期迭代后收敛停滞甚至陷入局部最优,可在迭代过程中加入增量梯度法,通过自适应步长法以提高重构过程对噪声的稳定性及鲁棒性[53]。最后,迭代恢复得到的复振幅被传播回物平面以使图像重新聚焦,从而产生清晰的聚焦强度与相位,可有效消除离焦模糊。此外,重构相位可用于生成显示样本相位梯度信息的数字差分干涉相衬结果、三维剖线信息及相衬结果,从而实现“数字多模态成像”。

3) 成像结果

如图10所示,无透镜全息显微镜CyteLive可获得具有清晰亚细胞结构的大视场定量相位成像结果,为活细胞高通量原位观测提供可能。

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图10 HeLa细胞的高通量重建定量相位结果

4) 系统软件

我们的自主开发系统配套软件如图11所示,图具有实时图像采集、相位重构、自动聚焦、差分干涉相衬、三维渲染等多模态显示功能,并可提供细胞计数、剖面分析等智能化细胞分析工具。可为活细胞研究提供智能化、自动化、易操作的友好交互窗口。

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图11 配套软件展示

4.未来展望

片上无透镜显微成像是一个极具发展前景的大视场高分辨率计算成像技术。它把高分辨率显微成像中对光学系统较高的硬件需求转化为可通过计算解决的问题。因此,可极大地缩小系统体积、降低系统成本、突破硬件物理限制。

“无透镜全息显微镜CyteLive”(图12)作为无透镜显微技术的初代产业化仪器[54],为实现面向床旁检验应用的高分辨、小型化、低成本、简单易用的显微设备提供一份蓝本。后续的仪器研制及相关产业化将有助于解决贫困地区疾病早期诊断困难的问题,有望为降低患病死亡率,改善医疗健康提供助力。

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图12 无透镜全息显微镜CyteLive实物展示

参考文献:

[1] F. Zernike, “Phase contrast, a new method for the microscopic observation of transparent objects part II,” Physica, vol. 9, no. 10, pp. 974–986, Dec. 1942, doi: 10.1016/S0031-8914(42)80079-8.

[2] G. Nomarski, “Differential microinterferometer with polarized waves,” J. Phys. Radium Paris, vol. 16, p. 9S, 1955.

[3] B. O. Leung and K. C. Chou, “Review of Super-Resolution Fluorescence Microscopy for Biology,” Appl Spectrosc, vol. 65, no. 9, pp. 967–980, Sep. 2011, doi: 10.1366/11-06398.

[4] E. Betzig et al., “Imaging Intracellular Fluorescent Proteins at Nanometer Resolution,” Science, vol. 313, no. 5793, pp. 1642–1645, Sep. 2006, doi: 10.1126/science.1127344.

[5] S. W. Hell and J. Wichmann, “Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy,” Opt. Lett., vol. 19, no. 11, p. 780, Jun. 1994, doi: 10.1364/OL.19.000780.

[6] S. W. Paddock, “Principles and Practices of Laser Scanning Confocal Microscopy,” MB, vol. 16, no. 2, pp. 127–150, 2000, doi: 10.1385/MB:16:2:127.

[7] M. Gu, Principles of three dimensional imaging in confocal microscopes. World Scientific, 1996.

[8] D. J. Stephens and V. J. Allan, “Light Microscopy Techniques for Live Cell Imaging,” Science, vol. 300, no. 5616, pp. 82–86, Apr. 2003, doi: 10.1126/science.1082160.

[9] 左超 and 陈钱, “计算光学成像: 何来, 何处, 何去, 何从?,” 红外与激光工程, vol. 51, no. 2, pp. 20220110–1, 2022.

[10] Sun Jiasong 孙佳嵩, Zhang Yuzhen 张玉珍, Chen Qian 陈钱, and Zuo Chao 左超, “Fourier Ptychographic Microscopy: Theory, Advances, and Applications,” 光学学报, vol. 36, no. 10, p. 1011005, 2016, doi: 10.3788/AOS201636.1011005.

[11] 张佳琳, 陈钱, 张翔宇, 孙佳嵩, and 左超, “无透镜片上显微成像技术: 理论, 发展与应用,” 红外与激光工程, vol. 48, no. 6, pp. 603009–0603009, 2019.

[12] W. Xu, M. H. Jericho, I. A. Meinertzhagen, and H. J. Kreuzer, “Digital in-line holography for biological applications,” Proc. Natl. Acad. Sci. U.S.A., vol. 98, no. 20, pp. 11301–11305, Sep. 2001, doi: 10.1073/pnas.191361398.

[13] X. Cui et al., “Lensless high-resolution on-chip optofluidic microscopes for Caenorhabditis elegans and cell imaging,” Proc. Natl. Acad. Sci. U.S.A., vol. 105, no. 31, pp. 10670–10675, Aug. 2008, doi: 10.1073/pnas.0804612105.

[14] T. Su, S. Seo, A. Erlinger, D. Tseng, and A. Ozcan, “Towards Wireless Health: Lensless On-Chip Cytometry,” p. 1.

[15] S. Seo, T.-W. Su, D. K. Tseng, A. Erlinger, and A. Ozcan, “Lensfree holographic imaging for on-chip cytometry and diagnostics,” Lab Chip, vol. 9, no. 6, pp. 777–787, 2009, doi: 10.1039/B813943A.

[16] S. A. Lee, R. Leitao, G. Zheng, S. Yang, A. Rodriguez, and C. Yang, “Color Capable Sub-Pixel Resolving Optofluidic Microscope and Its Application to Blood Cell Imaging for Malaria Diagnosis,” PLoS ONE, vol. 6, no. 10, p. e26127, Oct. 2011, doi: 10.1371/journal.pone.0026127.

[17] G. Zheng, S. A. Lee, Y. Antebi, M. B. Elowitz, and C. Yang, “The ePetri dish, an on-chip cell imaging platform based on subpixel perspective sweeping microscopy (SPSM),” Proceedings of the National Academy of Sciences, vol. 108, no. 41, pp. 16889–16894, Oct. 2011, doi: 10.1073/pnas.1110681108.

[18] S. Pang, X. Cui, J. DeModena, Y. M. Wang, P. Sternberg, and C. Yang, “Implementation of a color-capable optofluidic microscope on a RGB CMOS color sensor chip substrate,” Lab Chip, vol. 10, no. 4, p. 411, 2010, doi: 10.1039/b919004j.

[19] J. Garcia-Sucerquia, W. Xu, S. K. Jericho, P. Klages, M. H. Jericho, and H. J. Kreuzer, “Digital in-line holographic microscopy,” p. 15.

[20] J. Garcia-Sucerquia, W. Xu, M. H. Jericho, and H. J. Kreuzer, “Immersion digital in-line holographic microscopy,” Opt. Lett., vol. 31, no. 9, p. 1211, May 2006, doi: 10.1364/OL.31.001211.

[21] M. Kanka, R. Riesenberg, and H. J. Kreuzer, “Reconstruction of high-resolution holographic microscopic images,” Opt. Lett., vol. 34, no. 8, p. 1162, Apr. 2009, doi: 10.1364/OL.34.001162.

[22] M. Kanka, R. Riesenberg, P. Petruck, and C. Graulig, “High resolution (NA=08) in lensless in-line holographic microscopy with glass sample carriers,” Opt. Lett., vol. 36, no. 18, p. 3651, Sep. 2011, doi: 10.1364/OL.36.003651.

[23] O. Mudanyali et al., “Compact, light-weight and cost-effective microscope based on lensless incoherent holography for telemedicine applications,” Lab Chip, vol. 10, no. 11, p. 1417, 2010, doi: 10.1039/c000453g.

[24] W. Bishara, T.-W. Su, A. F. Coskun, and A. Ozcan, “Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution,” Opt. Express, vol. 18, no. 11, p. 11181, May 2010, doi: 10.1364/OE.18.011181.

[25] J. Hahn, S. Lim, K. Choi, R. Horisaki, and D. J. Brady, “Video-rate compressive holographic microscopic tomography,” Opt. Express, vol. 19, no. 8, p. 7289, Apr. 2011, doi: 10.1364/OE.19.007289.

[26] W. Luo, Y. Zhang, Z. Göröcs, A. Feizi, and A. Ozcan, “Propagation phasor approach for holographic image reconstruction,” Sci Rep, vol. 6, no. 1, p. 22738, Mar. 2016, doi: 10.1038/srep22738.

[27] Z. Xiong, J. E. Melzer, J. Garan, and E. McLeod, “Optimized sensing of sparse and small targets using lens-free holographic microscopy,” Opt. Express, vol. 26, no. 20, p. 25676, Oct. 2018, doi: 10.1364/OE.26.025676.

[28] T. E. Agbana, H. Gong, A. S. Amoah, V. Bezzubik, M. Verhaegen, and G. Vdovin, “Aliasing, coherence, and resolution in a lensless holographic microscope,” Opt. Lett., vol. 42, no. 12, p. 2271, Jun. 2017, doi: 10.1364/OL.42.002271.

[29] W. Zhang, L. Cao, G. Jin, and D. Brady, “Full field-of-view digital lens-free holography for weak-scattering objects based on grating modulation,” Appl. Opt., vol. 57, no. 1, p. A164, Jan. 2018, doi: 10.1364/AO.57.00A164.

[30] C. Allier et al., “Imaging of dense cell cultures by multiwavelength lens-free video microscopy: Cell Cultures by Lens-Free Microscopy,” Cytometry, vol. 91, no. 5, pp. 433–442, May 2017, doi: 10.1002/cyto.a.23079.

[31] E. Serabyn, K. Liewer, and J. K. Wallace, “Resolution optimization of an off-axis lensless digital holographic microscope,” Appl. Opt., vol. 57, no. 1, p. A172, Jan. 2018, doi: 10.1364/AO.57.00A172.

[32] S. Feng and J. Wu, “Resolution enhancement method for lensless in-line holographic microscope with spatially-extended light source,” Opt. Express, vol. 25, no. 20, p. 24735, Oct. 2017, doi: 10.1364/OE.25.024735.

[33] S. Feng, M. Wang, and J. Wu, “Lensless in-line holographic microscope with Talbot grating illumination,” Opt. Lett., vol. 41, no. 14, p. 3157, Jul. 2016, doi: 10.1364/OL.41.003157.

[34] Y. Rivenson, Y. Zhang, H. Günaydın, D. Teng, and A. Ozcan, “Phase recovery and holographic image reconstruction using deep learning in neural networks,” Light Sci Appl, vol. 7, no. 2, pp. 17141–17141, Feb. 2018, doi: 10.1038/lsa.2017.141.

[35] H. C. Koydemir et al., “Rapid imaging, detection and quantification of Giardia lamblia cysts using mobile-phone based fluorescent microscopy and machine learning,” Lab Chip, vol. 15, no. 5, pp. 1284–1293, 2015, doi: 10.1039/C4LC01358A.

[36] Z. S. Ballard, D. Shir, A. Bhardwaj, S. Bazargan, S. Sathianathan, and A. Ozcan, “Computational Sensing Using Low-Cost and Mobile Plasmonic Readers Designed by Machine Learning,” ACS Nano, vol. 11, no. 2, pp. 2266–2274, Feb. 2017, doi: 10.1021/acsnano.7b00105.

[37] Y. Ma, J. Wu, S. Chen, and L. Cao, “Explicit-restriction convolutional framework for lensless imaging,” Opt. Express, vol. 30, no. 9, p. 15266, Apr. 2022, doi: 10.1364/OE.456665.

[38] J. Zhang, J. Sun, Q. Chen, and C. Zuo, “Resolution Analysis in a Lens-Free On-Chip Digital Holographic Microscope,” IEEE Trans. Comput. Imaging, vol. 6, pp. 697–710, 2020, doi: 10.1109/TCI.2020.2964247.

[39] W. Bishara et al., “Holographic pixel super-resolution in portable lensless on-chip microscopy using a fiber-optic array,” Lab Chip, vol. 11, no. 7, p. 1276, 2011, doi: 10.1039/c0lc00684j.

[40] A. Greenbaum, A. Feizi, N. Akbari, and A. Ozcan, “Wide-field computational color imaging using pixel super-resolved on-chip microscopy,” Opt. Express, vol. 21, no. 10, p. 12469, May 2013, doi: 10.1364/OE.21.012469.

[41] A. Greenbaum, U. Sikora, and A. Ozcan, “Field-portable wide-field microscopy of dense samples using multi-height pixel super-resolution based lensfree imaging,” Lab Chip, vol. 12, no. 7, p. 1242, 2012, doi: 10.1039/c2lc21072j.

[42] G. Zheng, S. A. Lee, S. Yang, and C. Yang, “Sub-pixel resolving optofluidic microscope for on-chip cell imaging,” Lab Chip, vol. 10, no. 22, p. 3125, 2010, doi: 10.1039/c0lc00213e.

[43] J. Zhang, J. Sun, Q. Chen, J. Li, and C. Zuo, “Adaptive pixel-super-resolved lensfree in-line digital holography for wide-field on-chip microscopy,” Sci Rep, vol. 7, no. 1, p. 11777, Dec. 2017, doi: 10.1038/s41598-017-11715-x.

[44] J. Zhang, Q. Chen, J. Li, J. Sun, and C. Zuo, “Lensfree dynamic super-resolved phase imaging based on active micro-scanning,” Opt. Lett., vol. 43, no. 15, p. 3714, Aug. 2018, doi: 10.1364/OL.43.003714.

[45] W. Luo, Y. Zhang, A. Feizi, Z. Göröcs, and A. Ozcan, “Pixel super-resolution using wavelength scanning,” Light Sci Appl, vol. 5, no. 4, pp. e16060–e16060, Apr. 2016, doi: 10.1038/lsa.2016.60.

[46] X. Wu et al., “Wavelength-scanning lensfree on-chip microscopy for wide-field pixel-super-resolved quantitative phase imaging,” Opt. Lett., vol. 46, no. 9, p. 2023, May 2021, doi: 10.1364/OL.421869.

[47] W. Luo, Y. Zhang, A. Feizi, Z. Göröcs, and A. Ozcan, “Pixel super-resolution using wavelength scanning,” Light Sci Appl, vol. 5, no. 4, pp. e16060–e16060, Apr. 2016, doi: 10.1038/lsa.2016.60.

[48] C. Zuo, Q. Chen, and A. Asundi, “Boundary-artifact-free phase retrieval with the transport of intensity equation: fast solution with use of discrete cosine transform,” Opt. Express, vol. 22, no. 8, p. 9220, Apr. 2014, doi: 10.1364/OE.22.009220.

[49] S. S. Kou, L. Waller, G. Barbastathis, and C. J. R. Sheppard, “Transport-of-intensity approach to differential interference contrast (TI-DIC) microscopy for quantitative phase imaging,” Opt. Lett., vol. 35, no. 3, p. 447, Feb. 2010, doi: 10.1364/OL.35.000447.

[50] S. S. Gorthi and E. Schonbrun, “Phase imaging flow cytometry using a focus-stack collecting microscope,” Opt. Lett., vol. 37, no. 4, p. 707, Feb. 2012, doi: 10.1364/OL.37.000707.

[51] C. Zuo et al., “Transport of intensity equation: a tutorial,” Optics and Lasers in Engineering, vol. 135, p. 106187, Dec. 2020, doi: 10.1016/j.optlaseng.2020.106187.

[52] C. Zuo, J. Sun, J. Zhang, Y. Hu, and Q. Chen, “Lensless phase microscopy and diffraction tomography with multi-angle and multi-wavelength illuminations using a LED matrix,” Opt. Express, vol. 23, no. 11, p. 14314, Jun. 2015, doi: 10.1364/OE.23.014314.

[53] Y. Gao and L. Cao, “High-fidelity pixel-super-resolved complex field reconstruction via adaptive smoothing,” Opt. Lett., vol. 45, no. 24, p. 6807, Dec. 2020, doi: 10.1364/OL.409697.

[54] Y. Fan et al., “Smart computational light microscopes (SCLMs) of smart computational imaging laboratory (SCILab),” PhotoniX, vol. 2, no. 1, p. 19, Dec. 2021, doi: 10.1186/s43074-021-00040-2.


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