Biomedical optics express最新文献

Super resolution reconstruction of fluorescence microscopy images by a convolutional network with physical priors. 利用具有物理先验的卷积网络对荧光显微镜图像进行超分辨率重建。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-11-01 DOI: 10.1364/BOE.537589

Qiangyu Cai, Jun Lu, Wenting Gu, Di Xiao, Boyi Li, Lei Xu, Yuanjie Gu, Biqin Dong, Xin Liu

{"title":"Super resolution reconstruction of fluorescence microscopy images by a convolutional network with physical priors.","authors":"Qiangyu Cai, Jun Lu, Wenting Gu, Di Xiao, Boyi Li, Lei Xu, Yuanjie Gu, Biqin Dong, Xin Liu","doi":"10.1364/BOE.537589","DOIUrl":"10.1364/BOE.537589","url":null,"abstract":"Super-solution fluorescence microscopy, such as single-molecule localization microscopy (SMLM), is effective in observing subcellular structures and achieving excellent enhancement in spatial resolution in contrast to traditional fluorescence microscopy. Recently, deep learning has demonstrated excellent performance in SMLM in solving the trade-offs between spatiotemporal resolution, phototoxicity, and signal intensity. However, most of these researches rely on sufficient and high-quality datasets. Here, we propose a physical priors-based convolutional super-resolution network (PCSR), which incorporates a physical-based loss term and an initial optimization process based on the Wiener filter to create excellent super-resolution images directly using low-resolution images. The experimental results demonstrate that PCSR enables the achievement of a fast reconstruction time of 100 ms and a high spatial resolution of 10 nm by training on a limited dataset, allowing subcellular research with high spatiotemporal resolution, low cell phototoxic illumination, and high accessibility. In addition, the generalizability of PCSR to different live cell structures makes it a practical instrument for diverse cell research.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 11","pages":"6638-6653"},"PeriodicalIF":2.9,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11563314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142646994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Physics-guided deep learning-based real-time image reconstruction of Fourier-domain optical coherence tomography. 基于物理引导深度学习的傅立叶域光学相干断层扫描实时图像重建。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-10-30 eCollection Date: 2024-11-01 DOI: 10.1364/BOE.538756

Mengyuan Wang, Jianing Mao, Hang Su, Yuye Ling, Chuanqing Zhou, Yikai Su

{"title":"Physics-guided deep learning-based real-time image reconstruction of Fourier-domain optical coherence tomography.","authors":"Mengyuan Wang, Jianing Mao, Hang Su, Yuye Ling, Chuanqing Zhou, Yikai Su","doi":"10.1364/BOE.538756","DOIUrl":"10.1364/BOE.538756","url":null,"abstract":"In this paper, we introduce a physics-guided deep learning approach for high-quality, real-time Fourier-domain optical coherence tomography (FD-OCT) image reconstruction. Unlike traditional supervised deep learning methods, the proposed method employs unsupervised learning. It leverages the underlying OCT imaging physics to guide the neural networks, which could thus generate high-quality images and provide a physically sound solution to the original problem. Evaluations on synthetic and experimental datasets demonstrate the superior performance of our proposed physics-guided deep learning approach. The method achieves the highest image quality metrics compared to the inverse discrete Fourier transform (IDFT), the optimization-based methods, and several state-of-the-art methods based on deep learning. Our method enables real-time frame rates of 232 fps for synthetic images and 87 fps for experimental images, which represents significant improvements over existing techniques. Our physics-guided deep learning-based approach could offer a promising solution for FD-OCT image reconstruction, which potentially paves the way for leveraging the power of deep learning in real-world OCT imaging applications.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 11","pages":"6619-6637"},"PeriodicalIF":2.9,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11563334/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142646976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On bench evaluation of intraocular lenses: performance of a commercial interferometer. 眼内透镜的台架评估：商用干涉仪的性能。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-10-29 eCollection Date: 2024-11-01 DOI: 10.1364/BOE.540514

Noé Villemagne, Luc Joannes, Benjamin Stern, Damien Gatinel

引用次数: 0

Predictive coding compressive sensing optical coherence tomography hardware implementation. 预测编码压缩传感光学相干断层扫描硬件实现。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-10-29 eCollection Date: 2024-11-01 DOI: 10.1364/BOE.541685

Diego M Song Cho, Haiqiu Yang, Zizheng Jia, Arielle S Joasil, Xinran Gao, Christine P Hendon

引用次数: 0

Widefield optical coherence tomography by electro-optical modulation. 通过电子光学调制实现宽域光学相干断层成像。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-10-28 eCollection Date: 2024-11-01 DOI: 10.1364/BOE.540278

Dorian R Urban, Pavel Novak, Miguel A Preciado, Tom Vettenburg

{"title":"Widefield optical coherence tomography by electro-optical modulation.","authors":"Dorian R Urban, Pavel Novak, Miguel A Preciado, Tom Vettenburg","doi":"10.1364/BOE.540278","DOIUrl":"10.1364/BOE.540278","url":null,"abstract":"Optical coherence tomography (OCT) is a unique imaging modality capable of axial sectioning with a resolution of only a few microns. Its ability to image with high resolution deep within tissue makes it ideal for material inspection, dentistry, and, in particular, ophthalmology. Widefield retinal imaging has garnered increasing clinical interest for the detection of numerous retinal diseases. However, real-time applications in clinical practice demand the contrast of swept-source OCT at scan speeds that limit their depth range. The curvature of typical samples, such as teeth, corneas, or retinas, thus restricts the field-of-view of fast OCT systems. Novel high-speed swept sources are expected to further improve the scan rate; however, not without exacerbating the already severe trade-off in depth range. Here, we show how, without the need for mechanical repositioning, harmonic images can be rapidly synthesized at any depth. This is achieved by opto-electronic modulation of a single-frequency swept source laser in tandem with tailored numerical dispersion compensation. We demonstrate experimentally how real-time imaging of highly-curved samples is enabled by extending the effective depth-range 8-fold. Even at the scan speed of a 400 kHz swept source, harmonic OCT enables widefield retinal imaging.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 11","pages":"6573-6587"},"PeriodicalIF":2.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11563341/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142646999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of silicone-based phantoms for biomedical optics from 400 to 1550 nm. 开发用于 400 至 1550 纳米生物医学光学的硅基模型。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-10-28 eCollection Date: 2024-11-01 DOI: 10.1364/BOE.533481

Markus Wagner, Oliver Fugger, Florian Foschum, Alwin Kienle

引用次数: 0

Improving the scan throughput of polygon scanners. 提高多边形扫描仪的扫描吞吐量。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-10-25 eCollection Date: 2024-11-01 DOI: 10.1364/BOE.538757

Eric Hebert, Chris Xu

引用次数: 0

Visual simulation of intraocular lenses: from on-bench performance to computational and experimental validations. 眼内透镜的视觉模拟：从工作台性能到计算和实验验证。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-10-25 eCollection Date: 2024-11-01 DOI: 10.1364/BOE.538878

Petros Papadogiannis, Enrique Gambra, Grzegorz Łabuz, Weijia Yan, Diana Martín-Becerra, Irene Sisó-Fuertes, Alberto de Castro, Xoana Barcala, Gerd U Auffarth, Carlos Dorronsoro, Lucie Sawides

{"title":"Visual simulation of intraocular lenses: from on-bench performance to computational and experimental validations.","authors":"Petros Papadogiannis, Enrique Gambra, Grzegorz Łabuz, Weijia Yan, Diana Martín-Becerra, Irene Sisó-Fuertes, Alberto de Castro, Xoana Barcala, Gerd U Auffarth, Carlos Dorronsoro, Lucie Sawides","doi":"10.1364/BOE.538878","DOIUrl":"10.1364/BOE.538878","url":null,"abstract":"This study presents a systematic method to simulate various intraocular lenses (IOLs) available in the market. Five IOLs (two trifocals, one bifocal, one enhanced monofocal, and one extended depth of focus (EDOF)) were evaluated in terms of through focus visual Strehl (TFVS) utilizing the OptiSpheric IOL PRO2 device (Trioptics GmbH). Then, the estimated TFVS (ETFVS) and the temporal coefficients necessary for temporal multiplexing were computed, and through an iterative process, the SimVis TFVS was obtained. Finally, a high-speed focimeter was used to measure the opto-tunable lens responses to the temporal profile, and the experimental SimVis TFVS was acquired. Therefore, results are analyzed in terms of ETFVS (computed from the VSR-OTF), SimVis TFVS (computed from the TCs through temporal multiplexing), and experimental SimVis TFVS (acquired from the high-speed focimeter setup). The ETFVS and the SimVis TFVS curves demonstrated excellent alignment across all IOLs with cross-correlation coefficients > 0.94. Similarly, the experimental SimVis TFVS and the SimVis TFVS curves showed high correlation with cross-correlation coefficients > 0.97 and root mean square error (RMSE) < 0.05 for each lens. We demonstrated that different IOL designs can be visually simulated using its TFVS to obtain the corresponding temporal coefficients for simulations through temporal multiplexing using the SimVis technology.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 11","pages":"6521-6530"},"PeriodicalIF":2.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11563315/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142646998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Measurement of ocular aberration in noise based on deep learning with a Shack-Hartmann wavefront sensor. 利用 Shack-Hartmann 波前传感器，基于深度学习测量噪声中的眼球像差。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-10-25 eCollection Date: 2024-11-01 DOI: 10.1364/BOE.541483

Haobo Zhang, Yanrong Yang, Zitao Zhang, Chun Yin, Shengqian Wang, Kai Wei, Hao Chen, Junlei Zhao

{"title":"Measurement of ocular aberration in noise based on deep learning with a Shack-Hartmann wavefront sensor.","authors":"Haobo Zhang, Yanrong Yang, Zitao Zhang, Chun Yin, Shengqian Wang, Kai Wei, Hao Chen, Junlei Zhao","doi":"10.1364/BOE.541483","DOIUrl":"10.1364/BOE.541483","url":null,"abstract":"Shack-Hartmann-based wavefront sensing combined with deep learning, due to its fast, accurate, and large dynamic range, has been widely studied in many fields including ocular aberration measurement. Problems such as noise and corneal reflection affect the accuracy of detection in practical measuring ocular aberration systems. This paper establishes a framework comprising of a noise-added model, Hartmannograms with corneal reflections and the corneal reflection elimination algorithm. Therefore, a more realistic data set is obtained, enabling the convolutional neural network to learn more comprehensive features and carry out real machine verification. The results show that the proposed method has excellent measurement accuracy. The root mean square error (RMSE) of the residual wavefront is 0.00924 ± 0.0207λ (mean ± standard deviation) in simulation and 0.0496 ± 0.0156λ in a real machine. Compared with other methods, this network combined with the proposed corneal reflection elimination algorithm is more accurate, speedier, and more widely applicable in the noise and corneal reflection situations, making it a promising tool for ocular aberration measurement.","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 11","pages":"6531-6548"},"PeriodicalIF":2.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11563320/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142646971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pump-free SERS microfluidic chip based on an identification-competition strategy for ultrasensitive and efficient simultaneous detection of liver cancer-related microRNAs. 基于识别-竞争策略的无泵 SERS 微流控芯片，用于超灵敏、高效地同时检测肝癌相关 microRNAs。

IF 2.9 2区医学

Biomedical optics express Pub Date : 2024-10-24 eCollection Date: 2024-11-01 DOI: 10.1364/BOE.542523

Ruoyu Zhou, Guangfu Bai, Dongxu Zhu, Qiong Xu, Xudong Zhang, Tianran Li, Yayun Qian, Chiwen Bu

引用次数: 0