{"title":"Demonstrating a model-based edge detection and the impact of the illumination pupil’s discretization in optical microscopy","authors":"J. Krüger, R. Köning, B. Bodermann","doi":"10.1117/12.2600086","DOIUrl":"https://doi.org/10.1117/12.2600086","url":null,"abstract":"","PeriodicalId":431264,"journal":{"name":"Computational Optics 2021","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116626958","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}
As optical systems become smaller and requirements for packaging and functional performance demand more unique solutions to traditional imaging problems, the opportunity for exploration and advancement in simulation and design of non-traditional systems has grown considerably. For example, multi-layer diffractive elements and metalenses play a part in this new world of tiny optical systems, and in this paper we will explore some example system designs showing hybrid approaches from both traditional imaging and diffractive optical design, combined with more rigorous vector electromagnetic wave propagation. We will show combinations of phase optimization and subsequent nano-cell creation in full vector tools, as well as unique propagation of the electromagnetic field in combination from a rigorous model and a simplified beamlet-based decomposition approach. These tools can play a significant role in the design, optimization and analysis of these unique systems both now and in the future.
{"title":"Combined optimization, modeling and simulation techniques for non-traditional, next generation optics","authors":"M. Novak, B. Stone, Chenglin L. Xu","doi":"10.1117/12.2597190","DOIUrl":"https://doi.org/10.1117/12.2597190","url":null,"abstract":"As optical systems become smaller and requirements for packaging and functional performance demand more unique solutions to traditional imaging problems, the opportunity for exploration and advancement in simulation and design of non-traditional systems has grown considerably. For example, multi-layer diffractive elements and metalenses play a part in this new world of tiny optical systems, and in this paper we will explore some example system designs showing hybrid approaches from both traditional imaging and diffractive optical design, combined with more rigorous vector electromagnetic wave propagation. We will show combinations of phase optimization and subsequent nano-cell creation in full vector tools, as well as unique propagation of the electromagnetic field in combination from a rigorous model and a simplified beamlet-based decomposition approach. These tools can play a significant role in the design, optimization and analysis of these unique systems both now and in the future.","PeriodicalId":431264,"journal":{"name":"Computational Optics 2021","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116144607","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}
Shiqi Xu, Xiang Dai, Xi Yang, Kevin C Zhou, P. Konda, R. Horstmeyer
Microscopic imaging of anisotropic samples has many important applications in cytopathology. The endogenous contrast from the polarization properties of a specimen, such as its birefringence, provides valuable diagnostic information for several deadly diseases, including cardiac amyloidosis and squamous cell carcinoma, for example. In the past, polarized light microscopy (PLM) has been widely used as a diagnostic tool during the clinical review. However, in analogy with the standard microscope, the PLM typically has a restricted spatial-bandwidth product (SBP). As a consequence, one can either image a large area with low resolution or see the details of a very small area of the sample at the resolutions required for accurate analysis. To address the SBP issue of the PLM, we propose a computational microscopy method, termed vectorial Fourier ptychography, to illuminate the specimen with polarized light from different angles and detects different polarization states of the diffracted light. By illuminating a specimen with plane waves from different angles, our vectorial Fourier ptychography method effectively modulates the high-spatial-frequency components of the specimen into lower frequencies that can be detected by the optical system. With a Jones calculus-based forward model and a second-order phase retrieval method, we can reconstruct high-resolution, wide field-of-view(FOV) amplitude, phase, birefringence, retardance, and diattenuation of the specimen. To assess the reconstruction accuracy of our method, we imaged polystyrene beads submerged in immersion oils of different refractive index, as well as monosodium urate crystals. Further, To validate the diattenuation reconstruction accuracy, we reconstruct a USAF resolution test chart with a half blocked by a linear polarizer. These experiments confirm quantitatively accurate reconstruction results with a 1.25 um full-pitch resolution over a FOV of 6.6 x 4.4 mm^2, which is 5 times higher than the native (brightfield) resolution of the non-computational optical system. Finally, we demonstrate our technique by producing high SBP polarization images of several anisotropic biologic samples, includes collagen tissue, congo red stained cardiac tissue, and a bean root sample.
各向异性样品的显微成像在细胞病理学中有许多重要的应用。标本偏振特性的内源性对比，例如双折射，为几种致命疾病提供了有价值的诊断信息，例如心脏淀粉样变性和鳞状细胞癌。在过去，偏振光显微镜(PLM)被广泛用作临床检查中的诊断工具。然而，与标准显微镜类似，PLM通常具有有限的空间带宽积(SBP)。因此，人们可以以低分辨率成像大面积，也可以以精确分析所需的分辨率看到样品中非常小区域的细节。为了解决PLM的SBP问题，我们提出了一种称为矢量傅立叶平面摄影的计算显微镜方法，以偏振光从不同角度照射样品，并检测衍射光的不同偏振状态。通过用平面波从不同角度照射样品，我们的矢量傅立叶平面成像方法有效地将样品的高空间频率成分调制成光学系统可以检测到的较低频率。利用基于Jones演算的正演模型和二阶相位恢复方法，我们可以重建高分辨率、宽视场(FOV)的振幅、相位、双折射、延迟和双衰减。为了评估我们方法的重建准确性，我们对浸没在不同折射率的浸没油中的聚苯乙烯珠和尿酸钠晶体进行了成像。此外，为了验证双衰减重建的精度，我们重建了USAF分辨率测试图，其中一半被线性偏振器遮挡。这些实验证实了定量准确的重建结果，在6.6 x 4.4 mm^2的视场上，1.25 um的全间距分辨率比非计算光学系统的原生(明场)分辨率高5倍。最后，我们通过制作几种各向异性生物样品的高收缩压偏振图像来演示我们的技术，包括胶原组织、刚果红染色的心脏组织和豆根样本。
{"title":"Imaging anisotropy with vectorial Fourier ptychography","authors":"Shiqi Xu, Xiang Dai, Xi Yang, Kevin C Zhou, P. Konda, R. Horstmeyer","doi":"10.1117/12.2598999","DOIUrl":"https://doi.org/10.1117/12.2598999","url":null,"abstract":"Microscopic imaging of anisotropic samples has many important applications in cytopathology. The endogenous contrast from the polarization properties of a specimen, such as its birefringence, provides valuable diagnostic information for several deadly diseases, including cardiac amyloidosis and squamous cell carcinoma, for example. In the past, polarized light microscopy (PLM) has been widely used as a diagnostic tool during the clinical review. However, in analogy with the standard microscope, the PLM typically has a restricted spatial-bandwidth product (SBP). As a consequence, one can either image a large area with low resolution or see the details of a very small area of the sample at the resolutions required for accurate analysis. To address the SBP issue of the PLM, we propose a computational microscopy method, termed vectorial Fourier ptychography, to illuminate the specimen with polarized light from different angles and detects different polarization states of the diffracted light. By illuminating a specimen with plane waves from different angles, our vectorial Fourier ptychography method effectively modulates the high-spatial-frequency components of the specimen into lower frequencies that can be detected by the optical system. With a Jones calculus-based forward model and a second-order phase retrieval method, we can reconstruct high-resolution, wide field-of-view(FOV) amplitude, phase, birefringence, retardance, and diattenuation of the specimen. To assess the reconstruction accuracy of our method, we imaged polystyrene beads submerged in immersion oils of different refractive index, as well as monosodium urate crystals. Further, To validate the diattenuation reconstruction accuracy, we reconstruct a USAF resolution test chart with a half blocked by a linear polarizer. These experiments confirm quantitatively accurate reconstruction results with a 1.25 um full-pitch resolution over a FOV of 6.6 x 4.4 mm^2, which is 5 times higher than the native (brightfield) resolution of the non-computational optical system. Finally, we demonstrate our technique by producing high SBP polarization images of several anisotropic biologic samples, includes collagen tissue, congo red stained cardiac tissue, and a bean root sample.","PeriodicalId":431264,"journal":{"name":"Computational Optics 2021","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129958640","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}
A. Dejkameh, I. Mochi, R. Nebling, Hyun-su Kim, Tao Shen, Y. Ekinci
High-resolution imaging at short wavelengths from extreme ultraviolet to hard X-rays has many applications in a plethora of fields from astronomy to biology and semiconductor metrology. Unfortunately, efficient optics for these wavelengths are difficult to manufacture or have limited resolution. For this reason, in the past few years, coherent diffraction imaging (CDI) applications become widely used. In CDI, the object is illuminated by a coherent beam and the diffraction intensity is collected by a 2D pixel detector. In this process, the phase information of the diffracted light is lost. A phase retrieval algorithm is then used to reconstruct the object’s complex amplitude. Ptychography is a scanning version of coherent diffraction imaging and it is based on an iterative reconstruction algorithm that relies on the quality of the recorded diffraction intensity to converge. To obtain diffraction patterns with a high signal-to-noise ratio, a beam stop is used in many ptychography setups to avoid over-saturation and blooming effects on the detector. While using a beam stop in a ptychography setup has become common practice, the limits of affordable data loss due to beam stop have not been systematically investigated. Pixel masking is the conventional method to recover the lost frequencies. In this method, when enforcing the Fourier domain constraint, the invalid pixels are ignored. In the missing data region, the algorithm is allowed to keep the guess from the previous iteration. The illumination conditions of the ptychography experiment play a critical role in the signal recovery procedure. The diffraction pattern on the detector is the convolution of the Fourier transform of the object and the illumination. An illumination with a finite numerical aperture encodes the object information over a larger detector area. This makes the reconstruction algorithm more robust to pixel loss. We provide simulation and experimental results to demonstrate this theory.
{"title":"Missing frequency recovery through ptychography","authors":"A. Dejkameh, I. Mochi, R. Nebling, Hyun-su Kim, Tao Shen, Y. Ekinci","doi":"10.1117/12.2597060","DOIUrl":"https://doi.org/10.1117/12.2597060","url":null,"abstract":"High-resolution imaging at short wavelengths from extreme ultraviolet to hard X-rays has many applications in a plethora of fields from astronomy to biology and semiconductor metrology. Unfortunately, efficient optics for these wavelengths are difficult to manufacture or have limited resolution. For this reason, in the past few years, coherent diffraction imaging (CDI) applications become widely used. In CDI, the object is illuminated by a coherent beam and the diffraction intensity is collected by a 2D pixel detector. In this process, the phase information of the diffracted light is lost. A phase retrieval algorithm is then used to reconstruct the object’s complex amplitude. Ptychography is a scanning version of coherent diffraction imaging and it is based on an iterative reconstruction algorithm that relies on the quality of the recorded diffraction intensity to converge. To obtain diffraction patterns with a high signal-to-noise ratio, a beam stop is used in many ptychography setups to avoid over-saturation and blooming effects on the detector. While using a beam stop in a ptychography setup has become common practice, the limits of affordable data loss due to beam stop have not been systematically investigated. Pixel masking is the conventional method to recover the lost frequencies. In this method, when enforcing the Fourier domain constraint, the invalid pixels are ignored. In the missing data region, the algorithm is allowed to keep the guess from the previous iteration. The illumination conditions of the ptychography experiment play a critical role in the signal recovery procedure. The diffraction pattern on the detector is the convolution of the Fourier transform of the object and the illumination. An illumination with a finite numerical aperture encodes the object information over a larger detector area. This makes the reconstruction algorithm more robust to pixel loss. We provide simulation and experimental results to demonstrate this theory.","PeriodicalId":431264,"journal":{"name":"Computational Optics 2021","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132838847","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}
Abdalaziz Awad, Philipp Brendel, Dereje S. Woldeamanual, A. Rosskopf, A. Erdmann
We implement a data efficient approach to train a conditional generative adversarial network (cGAN) to predict 3D mask model aerial images, which involves providing the cGAN with approximated 2D mask model images as inputs and 3D mask model images as outputs. This approach takes advantage of the similarity between the images obtained from both computation models and the computational efficiency of the 2D mask model simulations, which allows the network to train on a reduced amount of training data compared to approaches previously implemented to accurately predict the 3D mask model images. We further demonstrate that the proposed method provides an accuracy improvement over training the network with the mask pattern layouts as inputs. Previous studies have shown that such cGAN architecture is proficient for generalized and complex image-to-image translation tasks. In this work, we demonstrate that adjustments to the weighing of the generator and discriminator losses can significantly improve the accuracy of the network from a lithographic standpoint Our initial tests indicate that only training the generator part of the cGAN can be beneficial to the accuracy while further reducing computational overhead. The accuracy of the network-generated 3D mask model images is demonstrated with low errors of typical lithographic process metrics, such as the critical dimensions and local contrast. The networks predictions also yield substantially reduced the errors compared to the 2D mask model while being on the same level of low computational demands.
{"title":"Accurate prediction of EUV lithographic images using data-efficient generative networks","authors":"Abdalaziz Awad, Philipp Brendel, Dereje S. Woldeamanual, A. Rosskopf, A. Erdmann","doi":"10.1117/12.2597309","DOIUrl":"https://doi.org/10.1117/12.2597309","url":null,"abstract":"We implement a data efficient approach to train a conditional generative adversarial network (cGAN) \u0000to predict 3D mask model aerial images, which involves providing the cGAN with approximated 2D mask model images as inputs and 3D mask model images as outputs. This approach takes advantage of the similarity between the images obtained from both computation models and the computational efficiency of the 2D mask model simulations, which allows the network to train on a reduced amount of training data compared to approaches previously implemented to accurately predict the 3D mask model images. We further demonstrate that the proposed method provides an accuracy improvement over training the network with the mask pattern layouts as inputs. \u0000Previous studies have shown that such cGAN architecture is proficient for generalized and complex image-to-image translation tasks. In this work, we demonstrate that adjustments to the weighing of the generator and discriminator losses can significantly improve the accuracy of the network from a lithographic standpoint Our initial tests indicate that only training the generator part of the cGAN can be beneficial to the accuracy while further reducing computational overhead. The accuracy of the network-generated 3D mask model images is demonstrated with low errors of typical lithographic process metrics, such as the critical dimensions and local contrast. The networks predictions also yield substantially reduced the errors compared to the 2D mask model while being on the same level of low computational demands.","PeriodicalId":431264,"journal":{"name":"Computational Optics 2021","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124748059","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}
{"title":"Welcome and Introduction to Conference 11875","authors":"Daniel G. Smith, F. Wyrowski, A. Erdmann","doi":"10.1117/12.2613784","DOIUrl":"https://doi.org/10.1117/12.2613784","url":null,"abstract":"","PeriodicalId":431264,"journal":{"name":"Computational Optics 2021","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125733750","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}
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