AIMC Topic: Mice

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3D Soma Detection in Large-Scale Whole Brain Images via a Two-Stage Neural Network.

IEEE transactions on medical imaging
3D soma detection in whole brain images is a critical step for neuron reconstruction. However, existing soma detection methods are not suitable for whole mouse brain images with large amounts of data and complex structure. In this paper, we propose a...

Noninvasive Tracking of Every Individual in Unmarked Mouse Groups Using Multi-Camera Fusion and Deep Learning.

Neuroscience bulletin
Accurate and efficient methods for identifying and tracking each animal in a group are needed to study complex behaviors and social interactions. Traditional tracking methods (e.g., marking each animal with dye or surgically implanting microchips) ca...

Automated quantification and statistical assessment of proliferating cardiomyocyte rates in embryonic hearts.

American journal of physiology. Heart and circulatory physiology
The use of digital image analysis and count regression models contributes to the reproducibility and rigor of histological studies in cardiovascular research. The use of formalized computer-based quantification strategies of histological images essen...

Cross-species cell-type assignment from single-cell RNA-seq data by a heterogeneous graph neural network.

Genome research
Cross-species comparative analyses of single-cell RNA sequencing (scRNA-seq) data allow us to explore, at single-cell resolution, the origins of the cellular diversity and evolutionary mechanisms that shape cellular form and function. Cell-type assig...

Population codes enable learning from few examples by shaping inductive bias.

eLife
Learning from a limited number of experiences requires suitable inductive biases. To identify how inductive biases are implemented in and shaped by neural codes, we analyze sample-efficient learning of arbitrary stimulus-response maps from arbitrary ...

Pattern recognition of topologically associating domains using deep learning.

BMC bioinformatics
BACKGROUND: Recent increasing evidence indicates that three-dimensional chromosome structure plays an important role in genomic function. Topologically associating domains (TADs) are self-interacting regions that have been shown to be a chromosomal s...

Scratch-AID, a deep learning-based system for automatic detection of mouse scratching behavior with high accuracy.

eLife
Mice are the most commonly used model animals for itch research and for development of anti-itch drugs. Most laboratories manually quantify mouse scratching behavior to assess itch intensity. This process is labor-intensive and limits large-scale gen...

Investigating Pose Representations and Motion Contexts Modeling for 3D Motion Prediction.

IEEE transactions on pattern analysis and machine intelligence
Predicting human motion from historical pose sequence is crucial for a machine to succeed in intelligent interactions with humans. One aspect that has been obviated so far, is the fact that how we represent the skeletal pose has a critical impact on ...

Volumetric imaging of fast cellular dynamics with deep learning enhanced bioluminescence microscopy.

Communications biology
Bioluminescence microscopy is an appealing alternative to fluorescence microscopy, because it does not depend on external illumination, and consequently does neither produce spurious background autofluorescence, nor perturb intrinsically photosensiti...

Deep Learning-Powered Bessel-Beam Multiparametric Photoacoustic Microscopy.

IEEE transactions on medical imaging
Enabling simultaneous and high-resolution quantification of the total concentration of hemoglobin ( [Formula: see text]), oxygen saturation of hemoglobin (sO2), and cerebral blood flow (CBF), multi-parametric photoacoustic microscopy (PAM) has emerge...