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Automated chondrocyte viability analysis of articular cartilage based on deep learning segmentation and classification of two-photon microscopic images 29

Automated chondrocyte viability analysis of articular cartil...

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Conference on three-dimensional and multidimensional microscopy - image acquisition and processing XXIX

作者： Fan, Hongming Xu, Pei Le, Michael Hsu, Jennifer Chen, Xun Li, Yang Zhang, Zhao Gao, Bruce Woolf, Shane Ye, Tong Clemson Univ Dept Bioengn Clemson SC 29634 USA Clemson Univ Sch Comp Clemson SC USA Med Univ South Carolina Dept Orthopaed & Phys Med Charleston SC 29425 USA Med Univ South Carolina Dept Regenerat Med & Cell Biol Charleston SC 29425 USA

ISBN: (纸本)9781510648043;9781510648036

Chondrocyte viability is an important measure to consider when assessing cartilage health. Dye-based cell viability assays are not suitable for in vivo or long-term studies. We have introduced a non-labeling viability assay based on the assessment of high-resolution images of cells and collagen structure using two-photon stimulated autofluorescence and second harmonic generation microscopy. By either the visual or quantitative assessment, we were able to differentiate living from dead chondrocytes in those images. However, both techniques require human participation and have limited throughputs. Throughput can be increased by using methods for automated cell-based image processing. Due to the poor image contrast, traditional image processing methods are ineffective on autofluorescence images produced by nonlinear microscopes. In this work, we examined chondrocyte segmentation and classification using Mask R-CNN, a deep learning approach to implement automated viability analysis. It has been demonstrated an 85% accuracy in chondrocyte viability assessment with proper training. This study demonstrates that automated and highly accurate image analysis is achievable with the use of deep learning methods. This image processing approach can be helpful to other imaging applications in clinical medicine and biological research.

关键词： nonlinear optical microscopy autofluorescence second harmonic generation deep learning viability

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Dual-view oblique plane microscopy for multi-well plate time-lapse 3D imaging assays in cancer research

Dual-view oblique plane microscopy for multi-well plate time...

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Novel Techniques in microscopy, NTM 2023 - Part of Optica Biophotonics Congress: Optics in the Life Sciences 2023

作者： Sparks, Hugh Dent, Lucas Ratcliffe, Colin D.H. Gustafsson, Nils Curry, Nathan Sahai, Erik Bakal, Chris Dunsby, Chris Photonics Group Department of Physics Imperial College London SW7 2AZ United Kingdom Cancer Stem Cell Team The Institute of Cancer Research LondonSW3 6JB United Kingdom Tumour Cell Biology Laboratory The Francis Crick Institute LondonNW1 1AT United Kingdom Centre for Pathology Faculty of Medicine Imperial College London SW7 2AZ United Kingdom

This talk introduces the development of an image acquisition and processing pipeline based on a dual-view oblique plane microscopy (dOPM) system and which is suitable for multi-well plate imaging assays for cancer res... 详细信息

ISBN: (纸本)9781957171210

关键词： High numerical aperture optics image processing microscopy Spatial resolution three dimensional imaging Time imaging

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three-dimensional and multidimensional microscopy: image acquisition and processing XXVI

Three-Dimensional and Multidimensional Microscopy: Image Acq...

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three-dimensional and multidimensional microscopy: image acquisition and processing XXVI 2019

ISBN: (纸本)9781510624085

The proceedings contain 20 papers. The topics discussed include: fluorescence recovery after photobleaching (FRAP) with simultaneous fluorescence lifetime and time-resolved fluorescence anisotropy imaging (FLIM & tr-FAIM);evaluation of a high-speed multispectral light source for stroboscopic differential imaging for endocardial examination of daphnia magna;fast stimulated Raman projection tomography with iterative reconstruction from sparse projections;Monte Carlo model for speckle contrast imaging;model-based iterative reconstruction for spectral-domain optical coherence tomography;and feasibility study of limited-angle reconstruction based in vivo optical projection tomography.

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Photoacoustic imaging with limited sampling: a review of machine learning approaches

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BIOMEDICAL OPTICS EXPRESS 2023年第4期14卷 1777-1799页

作者： Wang, Ruofan Zhu, Jing Xia, Jun Yao, Junjie Shi, Junhui LI, Chiye Zhejiang Lab Res Ctr Humanoid Sensing Hangzhou 311100 Peoples R China SUNY Buffalo Dept Biomed Engn Buffalo NY 14260 USA Duke Univ Dept Biomed Engn Durham NC 27708 USA

Photoacoustic imaging combines high optical absorption contrast and deep acoustic penetration, and can reveal structural, molecular, and functional information about biological tissue non-invasively. Due to practical restrictions, photoacoustic imaging systems often face various challenges, such as complex system configuration, long imaging time, and/or less-than-ideal image quality, which collectively hinder their clinical application. Machine learning has been applied to improve photoacoustic imaging and mitigate the otherwise strict requirements in system setup and data acquisition. In contrast to the previous reviews of learned methods in photoacoustic computed tomography (PACT), this review focuses on the application of machine learning approaches to address the limited spatial sampling problems in photoacoustic imaging, specifically the limited view and undersampling issues. We summarize the relevant PACT works based on their training data, workflow, and model architecture. Notably, we also introduce the recent limited sampling works on the other major implementation of photoacoustic imaging, i.e., photoacoustic microscopy (PAM). With machine learning-based processing, photoacoustic imaging can achieve improved image quality with modest spatial sampling, presenting great potential for low-cost and user-friendly clinical applications. (c) 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： image quality Imaging systems Medical imaging Optical absorption Optical imaging three dimensional imaging

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Parallel synthetic aperture transport-of-intensity diffraction tomography with annular illumination

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OPTICS LETTERS 2023年第7期48卷 1638-1641页

作者： Ullah, Habib Li, Jiaji Zhou, Shun Bai, Zhidong Ye, Ran Chen, Qian Zuo, Chao Nanjing Univ Sci & Technol Sch Elect & Opt Engn 200 Xiaolingwei St Nanjing 210094 Jiangsu Peoples R China Nanjing Univ Sci & Technol Jiangsu Key Lab Spectral Imaging & Intelligent Sen Nanjing 210094 Jiangsu Peoples R China Nanjing Univ Sci & Technol Smart Computat Imaging Lab SCILab Nanjing 210094 Jiangsu Peoples R China Nanjing Normal Univ Sch Comp & Elect Informat Nanjing 210023 Peoples R China

Transport-of-intensity diffraction tomography (TIDT) is a recently developed label-free computational microscopy technique that retrieves high-resolution three-dimensional (3D) refractive index (RI) distribution of biological speci-mens from 3D intensity-only measurements. However, the non-interferometric synthetic aperture in TIDT is gen-erally achieved sequentially through the acquisition of a large number of through-focus intensity stacks captured at different illumination angles, resulting in a very cum-bersome and redundant data acquisition process. To this end, we present a parallel implementation of a synthetic aperture in TIDT (PSA-TIDT) with annular illumination. We found that the matched annular illumination provides a mirror-symmetric 3D optical transfer function, indicating the analyticity in the upper half-plane of the complex phase function, which allows for recovery of the 3D RI from a sin-gle intensity stack. We experimentally validated PSA-TIDT by conducting high-resolution tomographic imaging of var-ious unlabeled biological samples, including human breast cancer cell lines (MCF-7), human hepatocyte carcinoma cell lines (HepG2), Henrietta Lacks (HeLa) cells, and red blood cells (RBCs).(c) 2023 Optica Publishing Group

关键词： Aperture synthesis LED lighting Speckle noise three dimensional image processing three dimensional measurement Tomography

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Low dosage 3D volume fluorescence microscopy imaging using compressive sensing 29

Low dosage 3D volume fluorescence microscopy imaging using c...

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Conference on three-dimensional and multidimensional microscopy - image acquisition and processing XXIX

作者： Mannam, Varun Brandt, Jacob Smith, Cody J. Howard, Scott Univ Notre Dame Dept Elect Engn Notre Dame IN 46556 USA Univ Notre Dame Dept Biol Sci Notre Dame IN 46556 USA

ISBN: (纸本)9781510648043;9781510648036

Fluorescence microscopy has been a significant tool to observe long-term imaging of embryos (in vivo) growth over time. However, cumulative exposure is phototoxic to such sensitive live samples. While techniques like light-sheet fluorescence microscopy (LSFM) allows for reduced exposure, it is not well suited for deep imaging models. Other computational techniques are computationally expensive and often lack restoration quality. To address this challenge, one can use various low-dosage imaging techniques that are developed to achieve the 3D volume reconstruction using a few slices in the axial direction (z-axis);however, they often lack restoration quality. Also, acquiring dense images (with small steps) in the axial direction is computationally expensive. To address this challenge, we present a compressive sensing (CS) based approach to fully reconstruct 3D volumes with the same signal-to-noise ratio (SNR) with less than half of the excitation dosage. We present the theory and experimentally validate the approach. To demonstrate our technique, we capture a 3D volume of the RFP labeled neurons in the zebrafish embryo spinal cord (30 mu m thickness) with the axial sampling of 0.1 mu m using a confocal microscope. From the results, we observe the CS-based approach achieves accurate 3D volume reconstruction from less than 20% of the entire stack optical sections. The developed CS-based methodology in this work can be easily applied to other deep imaging modalities such as two-photon and light-sheet microscopy, where reducing sample photo-toxicity is a critical challenge.

关键词： Low-dosage imaging 3D volume reconstruction fluorescence microscopy compressive sensing (CS) discrete cosine transform (DCT) deep imaging in vivo imaging

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Photoacoustic maximum amplitude projection microscopy by ultra-low data sampling

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OPTICS LETTERS 2023年第7期48卷 1718-1721页

作者： Cheng, Zhongwen Wang, Delin Zhang, Zhenhui Wang, Zhiyang Yang, Fei Zeng, Lvming Ji, Xuanrong Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipment Guangzhou 510006 Peoples R China South China Normal Univ MOE Key Lab Laser Life Sci Guangzhou 510631 Peoples R China South China Normal Univ Inst Laser Life Sci Guangzhou 510631 Peoples R China Jiangxi Sci & Technol Normal Univ Key Lab Opt Elect & Commun Nanchang 330038 Peoples R China

Photoacoustic microscopy (PAM) has attracted increasing research interest in the biomedical field due to its unique merit of combining light and sound. In general, the band-width of a photoacoustic signal reaches up to tens or even hundreds of MHz, which requires a high-performance acquisition card to meet the high requirement of precision of sampling and control. For most depth-insensitive scenes, it is complex and costly to capture the photoacoustic maximum amplitude projection (MAP) images. Herein, we propose a simple and low-cost MAP-PAM system based on a custom-made peak holding circuit to obtain the extremum values by Hz data sampling. The dynamic range of the input signal is 0.01-2.5 V, and the -6-dB bandwidth of the input signal can be up to 45 MHz. Through in vitro and in vivo experi-ments, we have verified that the system has the same imaging ability as conventional PAM. Owing to its compact size and ultra-low price (approximately $18), it provides a new per-formance paradigm for PAM and opens up a new way for an optimal photoacoustic sensing and imaging device.(c) 2023 Optica Publishing Group

关键词： image processing Medical imaging microscopy Optical imaging Photoacoustic imaging three dimensional imaging

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Validation of Excitation-Scan Hyperspectral Multi-faceted Mirror Array Prototype System Advancements to Hyperspectral Imaging Applications 29

Validation of Excitation-Scan Hyperspectral Multi-faceted Mi...

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Conference on three-dimensional and multidimensional microscopy - image acquisition and processing XXIX

作者： Parker, Marina Mayes, Sam A. Browning, Craig M. Deal, Joshua Gunn-Mayes, Samantha Rich, Thomas C. Leavesley, Silas J. Univ S Alabama Chem & Biomol Engn Mobile AL 36688 USA Univ S Alabama Pharmacol Mobile AL 36688 USA Univ S Alabama Ctr Lung Biol Mobile AL 36688 USA Univ S Alabama Dept Syst Engn Mobile AL 36688 USA

ISBN: (纸本)9781510648043;9781510648036

Hyperspectral imaging technologies (HSI) have undergone rapid development since their beginning stages. While original applications were in remote sensing, other uses include agriculture, food safety and medicine. HSI has shown great utility in fluorescence microscopy for detecting signatures from many fluorescent molecules;however, acquisitions speeds have been slow due to light losses associated with spectral filtering. Therefore, we designed a novel light emitting diode (LED)-based rapid excitation scanning hyperspectral imaging platform allowing users to obtain simultaneous measurements of fluorescent labels without compromising acquisition speeds. Previously, we reported our results of the optical ray trace simulations and the geometrical capability of designing a multifaceted mirror imaging system as an initial approach to combine light at many wavelengths. The design utilized LEDs and a multifaceted mirror array to combine light sources into a liquid light guide. The computational model was constructed using Monte Carlo optical ray software (TracePro, Lambda Research Corp.). Recent prototype validation results show that when compared to a commercial emission scanning spectral confocal microscope (Zeiss-LSM-980), the novel LED-based excitation scanning HSI prototype successfully detected and separated six fluorescent labels from a custom 6-label African green monkey kidney epithelial cells. We report on the prototype's ability to overcome limitations of acquisition speeds, sensitivity, and specificity present in conventional systems. Future work will evaluate prototype's light losses to determine latent design modifications needed to demonstrate the system's feasibility as a promising solution for overcoming HSI acquisition speeds. This work was supported by NSF award MRI1725937.

关键词： Systems Design LED Tissue imaging HSI Spectroscopy microscopy Transmission Spectral Fluorescence Molecules Cells

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Quantification of collagen networks in mammary tumors using TPEF and laser-based tomography 29

Quantification of collagen networks in mammary tumors using ...

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Conference on three-dimensional and multidimensional microscopy - image acquisition and processing XXIX

作者： Kamin, Hannes Nolte, Lena Maurer, Jochen Bleilevens, Andreas Stickeler, Elmar Johannsmeier, Sonja Heinemann, Dag Ripken, Tammo Laser Zentrum Hannover eV Ind & Biomed Opt Dept Hollerithallee 8 D-30419 Hannover Germany Univ Hosp Aachen Clin Gynecol & Obstet Pauwelstr 30 D-52074 Aachen Germany Lower Saxony Ctr Biomed Engn Implant Res & Dev NI Stadtfelddamm 34 D-30625 Hannover Germany Leibniz Univ Hannover Inst Hort Prod Syst Dept Phytophoton Herrenhauser Str 2 D-30419 Hannover Germany Leibniz Univ Hannover Hannover Ctr Opt Technol HOT Nienburger Str 17 D-30167 Hannover Germany

ISBN: (纸本)9781510648043;9781510648036

The triple-negative breast cancer (tnbc) is an aggressive subtype linked to a poor outcome of established breast cancer therapy. Increasing evidence points to the role of the tumor's extracellular matrix (ECM) as a determinant of its aggressiveness as well as the effectiveness of chemical therapeutics. three-dimensional imaging techniques can be used to unravel ECM architecture. Label-free contrast mechanisms such as second harmonic generation (SHG) avoid falsification and artifacts introduced by the labeling process. Here, we present the complementary use of two-photon excitation microscopy (TPEF) and Scanning Laser Optical Tomography (SLOT) for the investigation and quantification of tumor ECM. Both methods were used to capture fluorescence from antibody-labeled samples as well as the SHG signal from collagen strands in the ECM. SLOT generally allows for the investigation of larger samples of several mm up to a few cm in size. This work shows the capabilities of the tomographic setup compared to established TPEF, and demonstrates their combined use to maximize the information content of the acquired data. The obtained images served as a basis for ECM quantification. 3D-analysis allowed for determination of length, straightness and orientation of the collagen fibers based on fluorescence imaging as well as SHG imaging. The resulting coordinates might be used for synthetic reconstruction of a patient-specific tumor matrix, serving as a scaffold for pre-clinical therapeutic testing. Collagen imaging and quantification as presented here can therefore be employed for both basic and clinical research, paving the way for patient-specific cancer therapy.

关键词： cancer collagen imaging multimodal imaging extracellular matrix 3D imaging image reconstruction tomography second harmonic generation

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Self-Supervised Super-Resolution Approach for Isotropic Reconstruction of 3D Electron microscopy images from Anisotropic acquisition 11

Self-Supervised Super-Resolution Approach for Isotropic Reco...

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11th European Workshop on Visual Information processing, EUVIP 2023

作者： Khateri, Mohammad Ghahremani, Morteza Sierra, Alejandra Tohka, Jussi University of Eastern Finland A. I. Virtanen Institute for Molecular Sciences Finland

ISBN: (纸本)9798350342185

three-dimensional electron microscopy (3DEM) is an essential technique to investigate volumetric tissue ultrastructure. Due to technical limitations and high imaging costs, samples are often imaged anisotropically, where resolution in the axial direction (z) is lower than in the lateral directions (x, y). This anisotropy 3DEM can hamper subsequent analysis and visualization tasks. To overcome this limitation, we propose a novel deep-learning (DL)-based self-supervised super-resolution approach that computationally reconstructs isotropic 3DEM from the anisotropic acquisition. The proposed DL-based framework is built upon the U-shape architecture incorporating vision-transformer (ViT) blocks, enabling high-capability learning of local and global multi-scale image dependencies. To train the tailored network, we employ a self-supervised approach. Specifically, we generate pairs of anisotropic and isotropic training datasets from the given anisotropic 3DEM data. By feeding the given anisotropic 3DEM dataset in the trained network through our proposed framework, the isotropic 3DEM is obtained. Importantly, this isotropic reconstruction approach relies solely on the given anisotropic 3DEM dataset and does not require pairs of co-registered anisotropic and isotropic 3DEM training datasets. To evaluate the effectiveness of the proposed method, we conducted experiments using three 3DEM datasets acquired from brain. The experimental results demonstrated that our proposed framework could successfully reconstruct isotropic 3DEM from the anisotropic acquisition. © 2023 IEEE.

关键词： Anisotropy

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