AI Medical Compendium Topic

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Microscopy, Fluorescence

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Defining host-pathogen interactions employing an artificial intelligence workflow.

eLife
UNLABELLED: For image-based infection biology, accurate unbiased quantification of host-pathogen interactions is essential, yet often performed manually or using limited enumeration employing simple image analysis algorithms based on image segmentati...

Fluorescence microscopy image classification of 2D HeLa cells based on the CapsNet neural network.

Medical & biological engineering & computing
The development of computer technology now allows the quick and efficient automatic fluorescence microscopy generation of a large number of images of proteins in specific subcellular compartments using fluorescence microscopy. Digital image processin...

Cellular cartography of the organ of Corti based on optical tissue clearing and machine learning.

eLife
The highly organized spatial arrangement of sensory hair cells in the organ of Corti is essential for inner ear function. Here, we report a new analytical pipeline, based on optical clearing of tissue, for the construction of a single-cell resolution...

Gradients of three coastal environments off the South China Sea and their impacts on the dynamics of heterotrophic microbial communities.

The Science of the total environment
Heterotrophic fungus-like marine protists are recognized to contribute significantly to the coastal carbon cycling largely due to their high biomass and ability to decompose recalcitrant organic matter. Yet, little is known about their dynamics at po...

Deep learning enables cross-modality super-resolution in fluorescence microscopy.

Nature methods
We present deep-learning-enabled super-resolution across different fluorescence microscopy modalities. This data-driven approach does not require numerical modeling of the imaging process or the estimation of a point-spread-function, and is based on ...

Micro-Net: A unified model for segmentation of various objects in microscopy images.

Medical image analysis
Object segmentation and structure localization are important steps in automated image analysis pipelines for microscopy images. We present a convolution neural network (CNN) based deep learning architecture for segmentation of objects in microscopy i...

Structured illumination microscopy combined with machine learning enables the high throughput analysis and classification of virus structure.

eLife
Optical super-resolution microscopy techniques enable high molecular specificity with high spatial resolution and constitute a set of powerful tools in the investigation of the structure of supramolecular assemblies such as viruses. Here, we report o...

Performance of convolutional neural networks for identification of bacteria in 3D microscopy datasets.

PLoS computational biology
Three-dimensional microscopy is increasingly prevalent in biology due to the development of techniques such as multiphoton, spinning disk confocal, and light sheet fluorescence microscopies. These methods enable unprecedented studies of life at the m...

Analyzing complex single-molecule emission patterns with deep learning.

Nature methods
A fluorescent emitter simultaneously transmits its identity, location, and cellular context through its emission pattern. We developed smNet, a deep neural network for multiplexed single-molecule analysis to retrieve such information with high accura...

Rapid Quantification of Protein Particles in High-Concentration Antibody Formulations.

Journal of pharmaceutical sciences
Current technologies for monitoring the subvisible particles that may be generated during fill-finish operations for protein formulations are cumbersome. Measurement times are generally too long for real-time analysis, and the high protein concentrat...