AIMC Topic: Microscopy, Fluorescence

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Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging.

Nature communications
The process of protein aggregation, central to neurodegenerative diseases like Huntington's, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in d...

Highly adaptable deep-learning platform for automated detection and analysis of vesicle exocytosis.

Nature communications
Activity recognition in live-cell imaging is labor-intensive and requires significant human effort. Existing automated analysis tools are largely limited in versatility. We present the Intelligent Vesicle Exocytosis Analysis (IVEA) platform, an Image...

A modular fluorescent camera unit for wound imaging.

Communications biology
Advanced imaging tools are revolutionizing the diagnosis, treatment, and monitoring of medical conditions, offering unprecedented insights into live cell behavior and biophysical markers. We introduce a modular, hand-held fluorescent microscope featu...

CellSeg3D, Self-supervised 3D cell segmentation for fluorescence microscopy.

eLife
Understanding the complex three-dimensional structure of cells is crucial across many disciplines in biology and especially in neuroscience. Here, we introduce a set of models including a 3D transformer (SwinUNetR) and a novel 3D self-supervised lear...

An AI-assisted fluorescence microscopic system for screening mitophagy inducers by simultaneous analysis of mitophagic intermediates.

Nature communications
Mitophagy, the selective autophagic elimination of mitochondria, is essential for maintaining mitochondrial quality and cell homeostasis. Impairment of mitophagy flux, a process involving multiple sequential intermediates, is implicated in the onset ...

Pixel super-resolved virtual staining of label-free tissue using diffusion models.

Nature communications
Virtual staining of tissue offers a powerful tool for transforming label-free microscopy images of unstained tissue into equivalents of histochemically stained samples. This study presents a diffusion model-based pixel super-resolution virtual staini...

A Benchmark for Virus Infection Reporter Virtual Staining in Fluorescence and Brightfield Microscopy.

Scientific data
Detecting virus-infected cells in light microscopy requires a reporter signal commonly achieved by immunohistochemistry or genetic engineering. While classification-based machine learning approaches to the detection of virus-infected cells have been ...

A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts.

PloS one
Creating a dataset for training supervised machine learning algorithms can be a demanding task. This is especially true for blood vessel segmentation since one or more specialists are usually required for image annotation, and creating ground truth l...

Extensible Immunofluorescence (ExIF) accessibly generates high-plexity datasets by integrating standard 4-plex imaging data.

Nature communications
Standard immunofluorescence imaging captures just ~4 molecular markers (4-plex) per cell, limiting dissection of complex biology. Inspired by multimodal omics-based data integration approaches, we propose an Extensible Immunofluorescence (ExIF) frame...

Evaluating safe infrared neural stimulation parameters: Calcium dynamics and excitotoxicity thresholds in dorsal root ganglia neurons.

Journal of neuroscience methods
BACKGROUND: As a promising neural stimulation technique, infrared neural stimulation (INS) has recently gained significant attention due to its ability to stimulate neuronal activities without needing exogenous agents. NIR light is absorbed by water ...