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Microscopy

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Chemical crystal identification with deep learning machine vision.

BMC research notes
OBJECTIVE: This study was carried out with the purpose of testing the ability of deep learning machine vision to identify microscopic objects and geometries found in chemical crystal structures.

The application of convolution neural network based cell segmentation during cryopreservation.

Cryobiology
For most of the cells, water permeability and plasma membrane properties play a vital role in the optimal protocol for successful cryopreservation. Measuring the water permeability of cells during subzero temperature is essential. So far, there is no...

Live remote digital microscopy in peripheral blood smear evaluation: Intraobserver concordance and experience.

International journal of laboratory hematology
INTRODUCTION: Peripheral blood smear (PBS) review is a routine laboratory test which requires pathologist's interpretation when abnormal indices, atypical cells, or critical findings are identified. Real-time remote digital microscopy (DM) can potent...

A step towards intelligent EBSD microscopy: machine-learning prediction of twin activity in MgAZ31.

Journal of microscopy
UNLABELLED: Although microscopy is often treated as a quasi-static exercise for obtaining a snapshot of events and structure, it is clear that a more dynamic approach, involving real-time decision making for guiding the investigation process, may pro...

Contour-Seed Pairs Learning-Based Framework for Simultaneously Detecting and Segmenting Various Overlapping Cells/Nuclei in Microscopy Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we propose a novel contour-seed pairs learning-based framework for robust and automated cell/nucleus segmentation. Automated granular object segmentation in microscopy images has significant clinical importance for pathology grading of...

Hierarchical deep convolutional neural networks combine spectral and spatial information for highly accurate Raman-microscopy-based cytopathology.

Journal of biophotonics
Hierarchical variants of so-called deep convolutional neural networks (DCNNs) have facilitated breakthrough results for numerous pattern recognition tasks in recent years. We assess the potential of these novel whole-image classifiers for Raman-micro...

An open-source tool for analysis and automatic identification of dendritic spines using machine learning.

PloS one
Synaptic plasticity, the cellular basis for learning and memory, is mediated by a complex biochemical network of signaling proteins. These proteins are compartmentalized in dendritic spines, the tiny, bulbous, post-synaptic structures found on neuron...

Environmental properties of cells improve machine learning-based phenotype recognition accuracy.

Scientific reports
To answer major questions of cell biology, it is often essential to understand the complex phenotypic composition of cellular systems precisely. Modern automated microscopes produce vast amounts of images routinely, making manual analysis nearly impo...

Deep Learning for Drug Discovery and Cancer Research: Automated Analysis of Vascularization Images.

IEEE/ACM transactions on computational biology and bioinformatics
Likely drug candidates which are identified in traditional pre-clinical drug screens often fail in patient trials, increasing the societal burden of drug discovery. A major contributing factor to this phenomenon is the failure of traditional in vitro...