AIMC Topic: Mice

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Deep learning models for benign and malign ocular tumor growth estimation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Sep 8, 2021
Relatively abundant availability of medical imaging data has provided significant support in the development and testing of Neural Network based image processing methods. Clinicians often face issues in selecting suitable image processing algorithm f...
Reproducibility of Results Animals Neoplasms Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted Mice Tomography, Optical Coherence
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NeuriteNet: A convolutional neural network for assessing morphological parameters of neurite growth.

Journal of neuroscience methods Sep 2, 2021
BACKGROUND: During development or regeneration, neurons extend processes (i.e., neurites) via mechanisms that can be readily analyzed in culture. However, defining the impact of a drug or genetic manipulation on such mechanisms can be challenging due...
Animals Mice Neurons Neurites Neural Networks, Computer Neurogenesis
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DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels.

eLife Sep 2, 2021
Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological therapies. Behaviors of interest are often scored manually, which is time-consuming, limited to few ...
Image Processing, Computer-Assisted Mice Mice, Inbred C57BL Social Behavior Kinetics Drosophila melanogaster Walking Motor Activity Supervised Machine Learning Grooming Video Recording Female Pattern Recognition, Automated Humans Reproducibility of Results Neural Networks, Computer Animals Male
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Quantitative analysis of metastatic breast cancer in mice using deep learning on cryo-image data.

Scientific reports Sep 1, 2021
Cryo-imaging sections and images a whole mouse and provides ~ 120-GBytes of microscopic 3D color anatomy and fluorescence images, making fully manual analysis of metastases an onerous task. A convolutional neural network (CNN)-based metastases segmen...
Neural Networks, Computer Female Brain Neoplasms Lung Neoplasms Mice Bone Neoplasms Animals Mammary Neoplasms, Experimental Deep Learning Liver Neoplasms Image Processing, Computer-Assisted
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Mapping single-cell data to reference atlases by transfer learning.

Nature biotechnology Aug 30, 2021
Large single-cell atlases are now routinely generated to serve as references for analysis of smaller-scale studies. Yet learning from reference data is complicated by batch effects between datasets, limited availability of computational resources and...
SARS-CoV-2 Animals Deep Learning Single-Cell Analysis Mice Humans Datasets as Topic COVID-19 Reference Standards Organ Specificity
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CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice.

PLoS pathogens Aug 17, 2021
More humans have died of tuberculosis (TB) than any other infectious disease and millions still die each year. Experts advocate for blood-based, serum protein biomarkers to help diagnose TB, which afflicts millions of people in high-burden countries....
Mycobacterium tuberculosis Animals, Outbred Strains Chemokine CXCL1 Humans ROC Curve Machine Learning Mice Female Mice, Inbred C57BL Cytokines Animals Biomarkers Tuberculosis, Pulmonary Transcriptome
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An Improved Stacked Autoencoder for Metabolomic Data Classification.

Computational intelligence and neuroscience Aug 15, 2021
Naru3 (NR) is a traditional Mongolian medicine with high clinical efficacy and low incidence of side effects. Metabolomics is an approach that can facilitate the development of traditional drugs. However, metabolomic data have a high throughput, spar...
Support Vector Machine Algorithms Metabolomics Animals Mice
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Vesseg: An Open-Source Tool for Deep Learning-Based Atherosclerotic Plaque Quantification in Histopathology Images-Brief Report.

Arteriosclerosis, thrombosis, and vascular biology Aug 12, 2021
Objective: Manual plaque segmentation in microscopy images is a time-consuming process in atherosclerosis research and potentially subject to unacceptable user-to-user variability and observer bias. We address this by releasing Vesseg a tool that inc...
Plaque, Atherosclerotic Arteries Disease Models, Animal Mice, Inbred C57BL Predictive Value of Tests Atherosclerosis Microscopy Image Interpretation, Computer-Assisted Vascular Remodeling Mice, Knockout, ApoE Diagnosis, Computer-Assisted Deep Learning Software Mice Animals Staining and Labeling Female Male Reproducibility of Results Severity of Illness Index
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Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods.

Nature communications Aug 12, 2021
Efficient and precise base editors (BEs) for C-to-G transversion are highly desirable. However, the sequence context affecting editing outcome largely remains unclear. Here we report engineered C-to-G BEs of high efficiency and fidelity, with the seq...
Humans Machine Learning Female Reproducibility of Results Animals Binding Sites Codon HEK293 Cells Mice Gene Library Cytidine Deaminase Uracil-DNA Glycosidase Escherichia coli Base Sequence Caenorhabditis elegans CRISPR-Cas Systems Gene Editing
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Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Aug 10, 2021
Quantitative phase imaging (QPI) is an emerging label-free technique that produces images containing morphological and dynamical information without contrast agents. Unfortunately, the phase is wrapped in most imaging system. Phase unwrapping is the ...
Organoids Animals Deep Learning Algorithms Image Processing, Computer-Assisted Microscopy Mice Cells, Cultured Intestine, Small Holography Tissue Culture Techniques
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