AIMC Topic: Microscopy

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An end-to-end breast tumour classification model using context-based patch modelling - A BiLSTM approach for image classification.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Dec 4, 2020
Researchers working on computational analysis of Whole Slide Images (WSIs) in histopathology have primarily resorted to patch-based modelling due to large resolution of each WSI. The large resolution makes WSIs infeasible to be fed directly into the ...
Breast Neoplasms Models, Theoretical Microscopy Machine Learning Female Humans Neural Networks, Computer
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Super resolution microscopy and deep learning identify Zika virus reorganization of the endoplasmic reticulum.

Scientific reports Dec 1, 2020
The endoplasmic reticulum (ER) is a complex subcellular organelle composed of diverse structures such as tubules, sheets and tubular matrices. Flaviviruses such as Zika virus (ZIKV) induce reorganization of ER membranes to facilitate viral replicatio...
Microscopy Extracellular Matrix Zika Virus Deep Learning Cell Line, Tumor Organoids Endoplasmic Reticulum RNA, Double-Stranded Zika Virus Infection Viral Nonstructural Proteins Humans Brain
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A deep learning diagnostic platform for diffuse large B-cell lymphoma with high accuracy across multiple hospitals.

Nature communications Nov 26, 2020
Diagnostic histopathology is a gold standard for diagnosing hematopoietic malignancies. Pathologic diagnosis requires labor-intensive reading of a large number of tissue slides with high diagnostic accuracy equal or close to 100 percent to guide trea...
Humans Hematoxylin Image Interpretation, Computer-Assisted Eosine Yellowish-(YS) Diagnosis, Differential Deep Learning Coloring Agents Biopsy Lymphoma, Large B-Cell, Diffuse Microscopy Feasibility Studies Staining and Labeling Hospitals Lymph Nodes
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Detecting cells in intravital video microscopy using a deep convolutional neural network.

Computers in biology and medicine Nov 21, 2020
The analysis of leukocyte recruitment in intravital video microscopy (IVM) is essential to the understanding of inflammatory processes. However, because IVM images often present a large variety of visual characteristics, it is hard for an expert huma...
Machine Learning Image Processing, Computer-Assisted Microscopy, Video Microscopy Humans Neural Networks, Computer
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A convolutional neural network segments yeast microscopy images with high accuracy.

Nature communications Nov 12, 2020
The identification of cell borders ('segmentation') in microscopy images constitutes a bottleneck for large-scale experiments. For the model organism Saccharomyces cerevisiae, current segmentation methods face challenges when cells bud, crowd, or exh...
Software Image Processing, Computer-Assisted Saccharomyces cerevisiae Cell Cycle Microscopy Neural Networks, Computer
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Deeply-supervised density regression for automatic cell counting in microscopy images.

Medical image analysis Nov 11, 2020
Accurately counting the number of cells in microscopy images is required in many medical diagnosis and biological studies. This task is tedious, time-consuming, and prone to subjective errors. However, designing automatic counting methods remains cha...
Image Processing, Computer-Assisted Microscopy Neural Networks, Computer
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Deep learning in deep time.

Proceedings of the National Academy of Sciences of the United States of America Nov 9, 2020
Microscopy Pollen Fossils Neural Networks, Computer Deep Learning
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Learning Diatoms Classification from a Dry Test Slide by Holographic Microscopy.

Sensors (Basel, Switzerland) Nov 7, 2020
Diatoms are among the dominant phytoplankters in marine and freshwater habitats, and important biomarkers of water quality, making their identification and classification one of the current challenges for environmental monitoring. To date, taxonomy o...
Microscopy Holography Diatoms Neural Networks, Computer Machine Learning
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A large-scale optical microscopy image dataset of potato tuber for deep learning based plant cell assessment.

Scientific data Oct 27, 2020
We present a new large-scale three-fold annotated microscopy image dataset, aiming to advance the plant cell biology research by exploring different cell microstructures including cell size and shape, cell wall thickness, intercellular space, etc. in...
Solanum tuberosum Image Processing, Computer-Assisted Neural Networks, Computer Plant Cells Plant Tubers Microscopy Deep Learning
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Improving the taxonomy of fossil pollen using convolutional neural networks and superresolution microscopy.

Proceedings of the National Academy of Sciences of the United States of America Oct 23, 2020
Taxonomic resolution is a major challenge in palynology, largely limiting the ecological and evolutionary interpretations possible with deep-time fossil pollen data. We present an approach for fossil pollen analysis that uses optical superresolution ...
Microscopy Neural Networks, Computer South America Machine Learning Phylogeography Pollen Fossils Phylogeny Africa, Western Africa
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