AIMC Topic: Microscopy, Fluorescence
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Super-resolution biomedical imaging via reference-free statistical implicit neural representation.
Physics in medicine and biology
Oct 16, 2023
Supervised deep learning for image super-resolution (SR) has limitations in biomedical imaging due to the lack of large amounts of low- and high-resolution image pairs for model training. In this work, we propose a reference-free statistical implicit...
Localization and phenotyping of tuberculosis bacteria using a combination of deep learning and SVMs.
Computers in biology and medicine
Oct 13, 2023
Successful treatment of pulmonary tuberculosis (TB) depends on early diagnosis and careful monitoring of treatment response. Identification of acid-fast bacilli by fluorescence microscopy of sputum smears is a common tool for both tasks. Microscopy-b...
Analysis of cortical cell polarity by imaging flow cytometry.
Journal of cellular biochemistry
Sep 18, 2023
Metastasis is the main cause of cancer-related death and therapies specifically targeting metastasis are highly needed. Cortical cell polarity (CCP) is a prometastatic property of circulating tumor cells affecting their ability to exit blood vessels ...
Label-Free Intracellular Multi-Specificity in Yeast Cells by Phase-Contrast Tomographic Flow Cytometry.
Small methods
Sep 5, 2023
In-flow phase-contrast tomography provides a 3D refractive index of label-free cells in cytometry systems. Its major limitation, as with any quantitative phase imaging approach, is the lack of specificity compared to fluorescence microscopy, thus res...
Protocol for automated multivariate quantitative-image-based cytometry analysis by fluorescence microscopy of asynchronous adherent cells.
STAR protocols
Jul 13, 2023
Here, we present a protocol for multivariate quantitative-image-based cytometry (QIBC) analysis by fluorescence microscopy of asynchronous adherent cells. We describe steps for the preparation, treatment, and fixation of cells, sample staining, and i...
Deep learning enables fast, gentle STED microscopy.
Communications biology
Jun 27, 2023
STED microscopy is widely used to image subcellular structures with super-resolution. Here, we report that restoring STED images with deep learning can mitigate photobleaching and photodamage by reducing the pixel dwell time by one or two orders of m...
3D surface reconstruction of cellular cryo-soft X-ray microscopy tomograms using semisupervised deep learning.
Proceedings of the National Academy of Sciences of the United States of America
Jun 5, 2023
Cryo-soft X-ray tomography (cryo-SXT) is a powerful method to investigate the ultrastructure of cells, offering resolution in the tens of nanometer range and strong contrast for membranous structures without requiring labeling or chemical fixation. T...
Single-frame deep-learning super-resolution microscopy for intracellular dynamics imaging.
Nature communications
May 18, 2023
Single-molecule localization microscopy (SMLM) can be used to resolve subcellular structures and achieve a tenfold improvement in spatial resolution compared to that obtained by conventional fluorescence microscopy. However, the separation of single-...
Enhancing Total Optical Throughput of Microscopy with Deep Learning for Intravital Observation.
Small methods
May 15, 2023
The significance of performing large-depth dynamic microscopic imaging in vivo for life science research cannot be overstated. However, the optical throughput of the microscope limits the available information per unit of time, i.e., it is difficult ...
Active mesh and neural network pipeline for cell aggregate segmentation.
Biophysical journal
Mar 30, 2023
Segmenting cells within cellular aggregates in 3D is a growing challenge in cell biology due to improvements in capacity and accuracy of microscopy techniques. Here, we describe a pipeline to segment images of cell aggregates in 3D. The pipeline comb...
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