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Optical Imaging

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Artificial Intelligence in Multiphoton Tomography: Atopic Dermatitis Diagnosis.

Scientific reports
The diagnostic possibilities of multiphoton tomography (MPT) in dermatology have already been demonstrated. Nevertheless, the analysis of MPT data is still time-consuming and operator dependent. We propose a fully automatic approach based on convolut...

Efficient Position Decoding Methods Based on Fluorescence Calcium Imaging in the Mouse Hippocampus.

Neural computation
Large-scale fluorescence calcium imaging methods have become widely adopted for studies of long-term hippocampal and cortical neuronal dynamics. Pyramidal neurons of the rodent hippocampus show spatial tuning in freely foraging or head-fixed navigati...

Optimized Multimetal Sensitized Phosphor for Enhanced Red Up-Conversion Luminescence by Machine Learning.

ACS combinatorial science
In this research, machine learning including the genetic algorithm (GA) and support vector machine (SVM) algorithm is used to solve the "low up-conversion luminescence (UCL) intensity" problem in order to find the optimal phosphor with enhanced red U...

Machine learning for cluster analysis of localization microscopy data.

Nature communications
Quantifying the extent to which points are clustered in single-molecule localization microscopy data is vital to understanding the spatial relationships between molecules in the underlying sample. Many existing computational approaches are limited in...

Novel body fat estimation using machine learning and 3-dimensional optical imaging.

European journal of clinical nutrition
Estimates of body composition have been derived using 3-dimensional optical imaging (3DO), but no equations to date have been calibrated using a 4-component (4C) model criterion. This investigation reports the development of a novel body fat predicti...

Cellular and Molecular Probing of Intact Human Organs.

Cell
Optical tissue transparency permits scalable cellular and molecular investigation of complex tissues in 3D. Adult human organs are particularly challenging to render transparent because of the accumulation of dense and sturdy molecules in decades-age...

DeepSynth: Three-dimensional nuclear segmentation of biological images using neural networks trained with synthetic data.

Scientific reports
The scale of biological microscopy has increased dramatically over the past ten years, with the development of new modalities supporting collection of high-resolution fluorescence image volumes spanning hundreds of microns if not millimeters. The siz...

Fast fit-free analysis of fluorescence lifetime imaging via deep learning.

Proceedings of the National Academy of Sciences of the United States of America
Fluorescence lifetime imaging (FLI) provides unique quantitative information in biomedical and molecular biology studies but relies on complex data-fitting techniques to derive the quantities of interest. Herein, we propose a fit-free approach in FLI...

Inexpensive robotic system for standard and fluorescent imaging of protein crystals.

Acta crystallographica. Section F, Structural biology communications
Protein-crystallization imaging and classification is a labor-intensive process typically performed either by humans or by instruments that currently cost well over $100 000. This cost puts the use of crystallization-trial imaging outside the reach o...