
電子顕微鏡は光の代わりに加速された電子ビームを使用することで、光学顕微鏡よりも高い解像度と倍率を実現する。


coremsg

Hey it’s Professor Azam today my article about Electron Microscope 🔬

ELECTRON MICROSCOPE

高解像度の生物学的および非生物学的試料の画像を得るための電子顕微鏡

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The electron microscope is a powerful imaging device that uses a beam of accelerated electrons instead of light to achieve significantly higher resolution and magnification compared to optical microscopes.


electron-microscope-a-powerful-tool-for-high-resolution-imaging-of-microscopic-specimens


Electron Microscope: A Powerful Tool for High-Resolution Imaging of Microscopic Specimens



Proposing an unfolded accelerated projected-gradient descent procedure for image super-resolution and molecule localization problems in fluorescence microscopy.


algorithmic-unfolding-for-image-reconstruction-and-localization-in-fluorescence-microscopy


Algorithmic Unfolding for Image Reconstruction and Localization in Fluorescence Microscopy



Nellie is an automated pipeline for organelle segmentation, tracking, and feature extraction in live-cell microscopy.


nellie-automated-organelle-segmentation-and-feature-extraction-in-live-cell-microscopy


Nellie: Automated Organelle Segmentation and Feature Extraction in Live-Cell Microscopy



A novel method, denoiSplit, integrates image splitting and unsupervised denoising for improved microscopy analysis.


denoisplit-joint-image-splitting-and-unsupervised-denoising-method


denoiSplit: Joint Image Splitting and Unsupervised Denoising Method



Interactive data processing with a digital twin optimizes coordinate system alignment in 4D STEM microscopy.


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Calibrating Coordinate System Alignment in Scanning Transmission Electron Microscope Using Digital Twin



The author introduces MM3, a comprehensive image analysis pipeline for mother machine data, emphasizing the importance of understanding the limitations of different analysis methods to ensure accurate results.


Despite much progress, image processing remains a significant bottleneck for high-throughput analysis of microscopy data. One popular platform for single-cell time-lapse imaging is the mother machine, which enables long-term tracking of microbial cells under precisely controlled growth conditions. While several mother machine image analysis pipelines have been developed in the past several years, adoption by a non-expert audience remains a challenge. To fill this gap, we implemented our own software, MM3, as a plugin for the multidimensional image viewer napari. napari-MM3 is a complete and modular image analysis pipeline for mother machine data, which takes advantage of the high-level interactivity of napari. Here, we give an overview of napari-MM3 and test it against several well-designed and widely-used image analysis pipelines, including BACMMAN and DeLTA. Researchers often analyze mother machine data with custom scripts using varied image analysis methods, but a quantitative comparison of the output of different pipelines has been lacking. To this end, we show that key single-cell physiological parameter correlations and distributions are robust to the choice of analysis method. However, we also find that small changes in thresholding parameters can systematically alter parameters extracted from single-cell imaging experiments. Moreover, we explicitly show that in deep learning based segmentation, “what you put is what you get” (WYPIWYG) – i.e., pixel-level variation in training data for cell segmentation can propagate to the model output and bias spatial and temporal measurements. Finally, while the primary purpose of this work is to introduce the image analysis software that we have developed over the last decade in our lab, we also provide information for those who want to implement mother-machine-based high-throughput imaging and analysis methods in their research.

### Competing Interest Statement

The authors have declared no competing interest.

Tools and methods for high-throughput single-cell imaging with the mother machine

tools-and-methods-for-high-throughput-single-cell-imaging-with-the-mother-machine


Tools and Methods for High-Throughput Single-Cell Imaging with the Mother Machine



The author proposes a unified framework for microscopy defocus deblur using multi-pyramid transformer and contrastive learning to address challenges in microscopy deblur effectively.


A-Unified-Framework-for-Microscopy-Defocus-Deblur-with-Multi-Pyramid-Transformer-and-Contrastive-Learning


A Unified Framework for Microscopy Defocus Deblur with Multi-Pyramid Transformer and Contrastive Learning



The author presents the development of Open-Top Two-Photon Light Sheet Microscopy (OT-TP-LSM) as a non-destructive and high-throughput method for 3D pathology, enabling rapid and accurate visualization of cellular structures in various human cancer specimens.


Nondestructive pathology based on three-dimensional (3D) optical microscopy holds promise as a complement to traditional destructive hematoxylin and eosin (H&E) stained slide-based pathology by providing cellular information in high throughput manner. However, conventional techniques provided superficial information only due to shallow imaging depths. Herein, we developed open-top two-photon light sheet microscopy (OT-TP-LSM) for intraoperative 3D pathology. An extended depth of field two-photon excitation light sheet was generated by scanning a nondiffractive Bessel beam, and selective planar imaging was conducted with cameras at 400 frames/s max during the lateral translation of tissue specimens. Intrinsic second harmonic generation was collected for additional extracellular matrix (ECM) visualization. OT-TP-LSM was tested in various human cancer specimens including skin, pancreas, and prostate. High imaging depths were achieved owing to long excitation wavelengths and long wavelength fluorophores. 3D visualization of both cells and ECM enhanced the ability of cancer detection. Furthermore, an unsupervised deep learning network was employed for the style transfer of OT-TP-LSM images to virtual H&E images. The virtual H&E images exhibited comparable histological characteristics to real ones. OT-TP-LSM may have the potential for histopathological examination in surgical and biopsy applications by rapidly providing 3D information.

### Competing Interest Statement

The authors have declared no competing interest.

Open-top Bessel beam two-photon light sheet microscopy for three-dimensional pathology

Open-Top-Bessel-Beam-Two-Photon-Light-Sheet-Microscopy-for-3D-Pathology


Open-Top Bessel Beam Two-Photon Light Sheet Microscopy for 3D Pathology
