AIMC Topic: Microscopy
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Machine learning applications in cell image analysis.
Immunology and cell biology
Mar 15, 2017
Machine learning (ML) refers to a set of automatic pattern recognition methods that have been successfully applied across various problem domains, including biomedical image analysis. This review focuses on ML applications for image analysis in light...
Deep Learning Segmentation of Optical Microscopy Images Improves 3-D Neuron Reconstruction.
IEEE transactions on medical imaging
Mar 8, 2017
Digital reconstruction, or tracing, of 3-D neuron structure from microscopy images is a critical step toward reversing engineering the wiring and anatomy of a brain. Despite a number of prior attempts, this task remains very challenging, especially w...
Analysis of live cell images: Methods, tools and opportunities.
Methods (San Diego, Calif.)
Feb 27, 2017
Advances in optical microscopy, biosensors and cell culturing technologies have transformed live cell imaging. Thanks to these advances live cell imaging plays an increasingly important role in basic biology research as well as at all stages of drug ...
Objective detection of apoptosis in rat renal tissue sections using light microscopy and free image analysis software with subsequent machine learning: Detection of apoptosis in renal tissue.
Tissue & cell
Dec 28, 2016
OBJECTIVE: The current study proposes an automated machine learning approach for the quantification of cells in cell death pathways according to DNA fragmentation.
Morphological classification of odontogenic keratocysts using Bouligand-Minkowski fractal descriptors.
Computers in biology and medicine
Dec 8, 2016
The Odontogenic keratocyst (OKC) is a cystic lesion of the jaws, which has high growth and recurrence rates compared to other cysts of the jaws (for instance, radicular cyst, which is the most common jaw cyst type). For this reason OKCs are considere...
Automatic detection and classification of leukocytes using convolutional neural networks.
Medical & biological engineering & computing
Nov 7, 2016
The detection and classification of white blood cells (WBCs, also known as Leukocytes) is a hot issue because of its important applications in disease diagnosis. Nowadays the morphological analysis of blood cells is operated manually by skilled opera...
Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.
BioMed research international
Oct 26, 2016
In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically ...
Machine learning based methodology to identify cell shape phenotypes associated with microenvironmental cues.
Biomaterials
Jun 25, 2016
Cell morphology has been identified as a potential indicator of stem cell response to biomaterials. However, determination of cell shape phenotype in biomaterials is complicated by heterogeneous cell populations, microenvironment heterogeneity, and m...
The cellular microscopy phenotype ontology.
Journal of biomedical semantics
May 18, 2016
BACKGROUND: Phenotypic data derived from high content screening is currently annotated using free-text, thus preventing the integration of independent datasets, including those generated in different biological domains, such as cell lines, mouse and ...
Active machine learning-driven experimentation to determine compound effects on protein patterns.
eLife
Feb 3, 2016
High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or...
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