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Microscopy

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Pixel-to-Pixel Learning With Weak Supervision for Single-Stage Nucleus Recognition in Ki67 Images.

IEEE transactions on bio-medical engineering
OBJECTIVE: Nucleus recognition is a critical yet challenging step in histopathology image analysis, for example, in Ki67 immunohistochemistry stained images. Although many automated methods have been proposed, most use a multi-stage processing pipeli...

An effective and accurate identification system of Mycobacterium tuberculosis using convolution neural networks.

Microscopy research and technique
Tuberculosis (TB) remains the leading cause of morbidity and mortality from infectious disease in developing countries. The sputum smear microscopy remains the primary diagnostic laboratory test. However, microscopic examination is always time-consum...

Detection of Extended-Spectrum β-Lactamase-Producing Escherichia coli Using Infrared Microscopy and Machine-Learning Algorithms.

Analytical chemistry
The spread of multidrug resistant bacteria has become a global concern. One of the most important and emergent classes of multidrug-resistant bacteria is extended-spectrum β-lactamase-producing bacteria (ESBL-positive = ESBL). Due to widespread and c...

Application of deep convolutional neural networks in classification of protein subcellular localization with microscopy images.

Genetic epidemiology
Single-cell microscopy image analysis has proved invaluable in protein subcellular localization for inferring gene/protein function. Fluorescent-tagged proteins across cellular compartments are tracked and imaged in response to genetic or environment...

Deep Learning in Image Cytometry: A Review.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Artificial intelligence, deep convolutional neural networks, and deep learning are all niche terms that are increasingly appearing in scientific presentations as well as in the general media. In this review, we focus on deep learning and how it is ap...

Morphometric analysis of peripheral myelinated nerve fibers through deep learning.

Journal of the peripheral nervous system : JPNS
Irrespective of initial causes of neurological diseases, these disorders usually exhibit two key pathological changes-axonal loss or demyelination or a mixture of the two. Therefore, vigorous quantification of myelin and axons is essential in studyin...

Unsupervised Two-Path Neural Network for Cell Event Detection and Classification Using Spatiotemporal Patterns.

IEEE transactions on medical imaging
Automatic event detection in cell videos is essential for monitoring cell populations in biomedicine. Deep learning methods have advantages over traditional approaches for cell event detection due to their ability to capture more discriminative featu...

Large-Scale Multi-Class Image-Based Cell Classification With Deep Learning.

IEEE journal of biomedical and health informatics
Recent advances in ultra-high-throughput microscopy have enabled a new generation of cell classification methodologies using image-based cell phenotypes alone. In contrast to current single-cell analysis techniques that rely solely on slow and costly...

Acquisition and reconstruction of 4D surfaces of axolotl embryos with the flipping stage robotic microscope.

Bio Systems
We have designed and constructed a Flipping Stage for a light microscope that can view the whole exterior surface of a 2 mm diameter developing axolotl salamander embryo. It works by rapidly inverting the bottom-heavy embryo, imaging it as it rights ...