AIMC Topic: Intravital Microscopy

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Stable intracranial imaging of dura mater-engrafted pancreatic islet cells in awake mice.

Nature communications
By transplanting pancreatic islets onto the dura mater of the mouse brain, we establish a microscopy platform that enables longitudinal intravital imaging of otherwise optically inaccessible tissue. The system combines a cranial window with an air-cu...

Artificial intelligence strategies based on random forests for detecting ischemia-reperfusion injury changes in kidney tissue during intravital imaging.

Scientific reports
This study presents a supervised machine learning approach using a Random Forest classifier to detect ischemia-reperfusion injury (IRI) in kidney tissue based on intravital two-photon microscopy data. A rodent model of unilateral renal IRI was used, ...

Structured adaptive boosting trees for detection of multicellular aggregates in fluorescence intravital microscopy.

Microvascular research
Fluorescence intravital microscopy captures large data sets of dynamic multicellular interactions within various organs such as the lungs, liver, and brain of living subjects. In medical imaging, edge detection is used to accurately identify and deli...

Context-aware deep learning enables high-efficacy localization of high concentration microbubbles for super-resolution ultrasound localization microscopy.

Nature communications
Ultrasound localization microscopy (ULM) enables deep tissue microvascular imaging by localizing and tracking intravenously injected microbubbles circulating in the bloodstream. However, conventional localization techniques require spatially isolated...

Intravital microscopy visualizes innate immune crosstalk and function in tissue microenvironment.

European journal of immunology
Significant advances have been made in the field of intravital microscopy (IVM) on myeloid cells due to the growing number of validated fluorescent probes and reporter mice. IVM provides a visualization platform to directly observe cell behavior and ...

Enhancing Total Optical Throughput of Microscopy with Deep Learning for Intravital Observation.

Small methods
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 ...

ACME: Automatic feature extraction for cell migration examination through intravital microscopy imaging.

Medical image analysis
Cell detection and tracking applied to in vivo fluorescence microscopy has become an essential tool in biomedicine to characterize 4D (3D space plus time) biological processes at the cellular level. Traditional approaches to cell motion analysis by m...

A machine learning approach for single cell interphase cell cycle staging.

Scientific reports
The cell nucleus is a tightly regulated organelle and its architectural structure is dynamically orchestrated to maintain normal cell function. Indeed, fluctuations in nuclear size and shape are known to occur during the cell cycle and alterations in...

Two-step machine learning method for the rapid analysis of microvascular flow in intravital video microscopy.

Scientific reports
Microvascular blood flow is crucial for tissue and organ function and is often severely affected by diseases. Therefore, investigating the microvasculature under different pathological circumstances is essential to understand the role of the microcir...

Early Emergence of Solid Shape Coding in Natural and Deep Network Vision.

Current biology : CB
Area V4 is the first object-specific processing stage in the ventral visual pathway, just as area MT is the first motion-specific processing stage in the dorsal pathway. For almost 50 years, coding of object shape in V4 has been studied and conceived...