AI Medical Compendium Topic

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Microscopy, Fluorescence

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Molecular imaging with neural training of identification algorithm (neural network localization identification).

Microscopy research and technique
Superresolution localization microscopy strongly relies on robust identification algorithms for accurate reconstruction of the biological systems it is used to measure. The fields of machine learning and computer vision have provided promising soluti...

Developing Noise-Resistant Three-Dimensional Single Particle Tracking Using Deep Neural Networks.

Analytical chemistry
Three-dimensional single particle tracking (3D SPT) is a powerful tool in various chemical and biological studies. In 3D SPT, z sensitive point spread functions (PSFs) are frequently used to generate different patterns, from which the axial position ...

Deep learning is combined with massive-scale citizen science to improve large-scale image classification.

Nature biotechnology
Pattern recognition and classification of images are key challenges throughout the life sciences. We combined two approaches for large-scale classification of fluorescence microscopy images. First, using the publicly available data set from the Cell ...

A Novel Morphological Marker for the Analysis of Molecular Activities at the Single-cell Level.

Cell structure and function
For more than a century, hematoxylin and eosin (H&E) staining has been the de facto standard for histological studies. Consequently, the legacy of histological knowledge is largely based on H&E staining. Due to the recent advent of multi-photon excit...

Tracing cell lineages in videos of lens-free microscopy.

Medical image analysis
In vitro experiments with cultured cells are essential for studying their growth and migration pattern and thus, for gaining a better understanding of cancer progression and its treatment. Recent progress in lens-free microscopy (LFM) has rendered it...

Deep learning massively accelerates super-resolution localization microscopy.

Nature biotechnology
The speed of super-resolution microscopy methods based on single-molecule localization, for example, PALM and STORM, is limited by the need to record many thousands of frames with a small number of observed molecules in each. Here, we present ANNA-PA...

Noninvasive detection of macrophage activation with single-cell resolution through machine learning.

Proceedings of the National Academy of Sciences of the United States of America
We present a method enabling the noninvasive study of minute cellular changes in response to stimuli, based on the acquisition of multiple parameters through label-free microscopy. The retrieved parameters are related to different attributes of the c...

A robotic multidimensional directed evolution approach applied to fluorescent voltage reporters.

Nature chemical biology
We developed a new way to engineer complex proteins toward multidimensional specifications using a simple, yet scalable, directed evolution strategy. By robotically picking mammalian cells that were identified, under a microscope, as expressing prote...

Efficient computational model for classification of protein localization images using Extended Threshold Adjacency Statistics and Support Vector Machines.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Discriminative and informative feature extraction is the core requirement for accurate and efficient classification of protein subcellular localization images so that drug development could be more effective. The objective o...