AIMC Topic: Microscopy

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Cytopathological image analysis using deep-learning networks in microfluidic microscopy.

Journal of the Optical Society of America. A, Optics, image science, and vision Jan 1, 2017
Cytopathologic testing is one of the most critical steps in the diagnosis of diseases, including cancer. However, the task is laborious and demands skill. Associated high cost and low throughput drew considerable interest in automating the testing pr...
Image Processing, Computer-Assisted Microfluidics Machine Learning Algorithms HL-60 Cells K562 Cells Microscopy Precursor Cell Lymphoblastic Leukemia-Lymphoma Humans Neural Networks, Computer
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Rapid, portable and cost-effective yeast cell viability and concentration analysis using lensfree on-chip microscopy and machine learning.

Lab on a chip Nov 1, 2016
Monitoring yeast cell viability and concentration is important in brewing, baking and biofuel production. However, existing methods of measuring viability and concentration are relatively bulky, tedious and expensive. Here we demonstrate a compact an...
Machine Learning Saccharomyces cerevisiae Holography Microscopy Cost-Benefit Analysis Time Factors
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Automatic classification of cancer cells in multispectral microscopic images of lymph node samples.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Histopathological analysis is crucial for the diagnosis of a large number of cancer types. A lot of progress has been made in the development of molecular based assays, but many of the cases still require the careful analysis of the stained tissue un...
Cell Nucleus Automation Breast Neoplasms Algorithms Humans Lymph Nodes Image Processing, Computer-Assisted Female Microscopy
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Classifying and segmenting microscopy images with deep multiple instance learning.

Bioinformatics (Oxford, England) Jun 15, 2016
MOTIVATION: High-content screening (HCS) technologies have enabled large scale imaging experiments for studying cell biology and for drug screening. These systems produce hundreds of thousands of microscopy images per day and their utility depends on...
Microscopy Image Interpretation, Computer-Assisted Yeasts Machine Learning Algorithms Neural Networks, Computer Humans
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PHOCOS: inferring multi-feature phenotypic crosstalk networks.

Bioinformatics (Oxford, England) Jun 15, 2016
MOTIVATION: Quantification of cellular changes to perturbations can provide a powerful approach to infer crosstalk among molecular components in biological networks. Existing crosstalk inference methods conduct network-structure learning based on a s...
Biomarkers Signal Transduction Machine Learning Phenotype Receptor Cross-Talk Neutrophils Microscopy Humans
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Automatic identification of fungi under complex microscopic fecal images.

Journal of biomedical optics Jul 1, 2015
Automatic identification of fungi in microscopic fecal images provides important information for evaluating digestive diseases. To date, disease diagnosis is primarily performed by manual techniques. However, the accuracy of this approach depends on ...
Fungi Mycological Typing Techniques Humans Microscopy Feces Neural Networks, Computer Image Processing, Computer-Assisted
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Robust supervised segmentation of neuropathology whole-slide microscopy images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jan 1, 2015
Alzheimer's disease is characterized by brain pathological aggregates such as Aβ plaques and neurofibrillary tangles which trigger neuroinflammation and participate to neuronal loss. Quantification of these pathological markers on histological sectio...
Microscopy Signal-To-Noise Ratio Neurofibrillary Tangles Plaque, Amyloid Supervised Machine Learning Alzheimer Disease Color Humans Brain Animals Image Processing, Computer-Assisted Mice
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