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Microscopy, Fluorescence

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Improving flat fluorescence microscopy in scattering tissue through deep learning strategies.

Optics express
Intravital microscopy in small animals growingly contributes to the visualization of short- and long-term mammalian biological processes. Miniaturized fluorescence microscopy has revolutionized the observation of live animals' neural circuits. The te...

Protocol for automated multivariate quantitative-image-based cytometry analysis by fluorescence microscopy of asynchronous adherent cells.

STAR protocols
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...

Analysis of cortical cell polarity by imaging flow cytometry.

Journal of cellular biochemistry
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
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...

Super-resolution biomedical imaging via reference-free statistical implicit neural representation.

Physics in medicine and biology
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
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...

Automated quantification of vacuole fusion and lipophagy in from fluorescence and cryo-soft X-ray microscopy data using deep learning.

Autophagy
During starvation in the yeast vacuolar vesicles fuse and lipid droplets (LDs) can become internalized into the vacuole in an autophagic process named lipophagy. There is a lack of tools to quantitatively assess starvation-induced vacuole fusion and...

Live-cell imaging in the deep learning era.

Current opinion in cell biology
Live imaging is a powerful tool, enabling scientists to observe living organisms in real time. In particular, when combined with fluorescence microscopy, live imaging allows the monitoring of cellular components with high sensitivity and specificity....

FiCRoN, a deep learning-based algorithm for the automatic determination of intracellular parasite burden from fluorescence microscopy images.

Medical image analysis
Protozoan parasites are responsible for dramatic, neglected diseases. The automatic determination of intracellular parasite burden from fluorescence microscopy images is a challenging problem. Recent advances in deep learning are transforming this pr...

Deep UV-excited fluorescence microscopy installed with CycleGAN-assisted image translation enhances precise detection of lymph node metastasis towards rapid intraoperative diagnosis.

Scientific reports
Rapid and precise intraoperative diagnosing systems are required for improving surgical outcomes and patient prognosis. Because of the poor quality and time-intensive process of the prevalent frozen section procedure, various intraoperative diagnosti...