AIMC Topic: Microscopy

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Deep learning enables pathologist-like scoring of NASH models.

Scientific reports Dec 5, 2019
Non-alcoholic fatty liver disease (NAFLD) and the progressive form of non-alcoholic steatohepatitis (NASH) are diseases of major importance with a high unmet medical need. Efficacy studies on novel compounds to treat NAFLD/NASH using disease models a...
Animals Severity of Illness Index Deep Learning Humans Biopsy Feasibility Studies Image Processing, Computer-Assisted Disease Models, Animal Mice Liver Non-alcoholic Fatty Liver Disease Microscopy Rats Datasets as Topic
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Epithelium segmentation and automated Gleason grading of prostate cancer via deep learning in label-free multiphoton microscopic images.

Journal of biophotonics Dec 4, 2019
In the current clinical care practice, Gleason grading system is one of the most powerful prognostic predictors for prostate cancer (PCa). The grading system is based on the architectural pattern of cancerous epithelium in histological images. Howeve...
Humans Male Neoplasm Grading Epithelium Microscopy Deep Learning Prostatic Neoplasms
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ImageDataExtractor: A Tool To Extract and Quantify Data from Microscopy Images.

Journal of chemical information and modeling Dec 3, 2019
The rise of data science is leading to new paradigms in data-driven materials discovery. This carries an essential notion that large data sources containing chemical structure and property information can be mined in a fashion that detects and exploi...
Microscopy Neural Networks, Computer Image Processing, Computer-Assisted
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Human peripheral blood leukocyte classification method based on convolutional neural network and data augmentation.

Medical physics Nov 22, 2019
PURPOSE: Human peripheral blood leukocytes' classification is important for diagnosing blood diseases. Many microscopic leukocyte image automatic detection methods are proposed. In recent years, convolutional neural networks (CNNs) are applied to mic...
Neural Networks, Computer Image Processing, Computer-Assisted Leukocytes Humans Microscopy
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Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides.

JAMA network open Nov 1, 2019
IMPORTANCE: Deep learning-based methods, such as the sliding window approach for cropped-image classification and heuristic aggregation for whole-slide inference, for analyzing histological patterns in high-resolution microscopy images have shown pro...
Barrett Esophagus Adenocarcinoma Biopsy Microscopy Datasets as Topic Esophageal Neoplasms Computer Simulation Deep Learning Humans Neural Networks, Computer
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Urine Sediment Recognition Method Based on Multi-View Deep Residual Learning in Microscopic Image.

Journal of medical systems Oct 23, 2019
Urine sediment recognition is attracting growing interest in the field of computer vision. A multi-view urine cell recognition method based on multi-view deep residual learning is proposed to solve some existing problems, such as multi-view cell gray...
Deep Learning Image Processing, Computer-Assisted Humans Microscopy Pattern Recognition, Automated Urinalysis
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Cell Type Classification and Unsupervised Morphological Phenotyping From Low-Resolution Images Using Deep Learning.

Scientific reports Sep 17, 2019
Convolutional neural networks (ConvNets) have proven to be successful in both the classification and semantic segmentation of cell images. Here we establish a method for cell type classification utilizing images taken with a benchtop microscope direc...
Algorithms Phenotype Deep Learning Neural Networks, Computer Microscopy Single-Cell Analysis Organ Specificity Models, Theoretical Cell Tracking
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Towards pixel-to-pixel deep nucleus detection in microscopy images.

BMC bioinformatics Sep 14, 2019
BACKGROUND: Nucleus is a fundamental task in microscopy image analysis and supports many other quantitative studies such as object counting, segmentation, tracking, etc. Deep neural networks are emerging as a powerful tool for biomedical image comput...
Microscopy Image Interpretation, Computer-Assisted Humans Neural Networks, Computer
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Predicting the future direction of cell movement with convolutional neural networks.

PloS one Sep 4, 2019
Image-based deep learning systems, such as convolutional neural networks (CNNs), have recently been applied to cell classification, producing impressive results; however, application of CNNs has been confined to classification of the current cell sta...
Time-Lapse Imaging Mice Cell Movement Microscopy NIH 3T3 Cells Humans Animals Cell Line Neural Networks, Computer Image Processing, Computer-Assisted
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Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting.

PLoS computational biology Sep 3, 2019
Cellular microscopy images contain rich insights about biology. To extract this information, researchers use features, or measurements of the patterns of interest in the images. Here, we introduce a convolutional neural network (CNN) to automatically...
Humans Microscopy Yeasts Single-Cell Analysis Neural Networks, Computer Cells, Cultured Computational Biology Unsupervised Machine Learning Image Processing, Computer-Assisted
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