AIMC Topic: Animals

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DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels.

eLife
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 ...

A CNN-based method to reconstruct 3-D spine surfaces from US images in vivo.

Medical image analysis
Three-dimensional (3-D) reconstruction of the spine surface is of strong clinical relevance for the diagnosis and prognosis of spine disorders and intra-operative image guidance. In this paper, we report a new technique to reconstruct lumbar spine su...

Leveraging advances in immunopathology and artificial intelligence to analyze in vitro tumor models in composition and space.

Advanced drug delivery reviews
Cancer is the leading cause of death worldwide. Unfortunately, efforts to understand this disease are confounded by the complex, heterogenous tumor microenvironment (TME). Better understanding of the TME could lead to novel diagnostic, prognostic, an...

Quantitative analysis of metastatic breast cancer in mice using deep learning on cryo-image data.

Scientific reports
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...

Electromechanical Wave Imaging With Machine Learning for Automated Isochrone Generation.

IEEE transactions on medical imaging
Standard Electromechanical Wave Imaging isochrone generation relies on manual selection of zero-crossing (ZC) locations on incremental strain curves for a number of pixels in the segmented myocardium for each echocardiographic view and patient. When ...

Mapping single-cell data to reference atlases by transfer learning.

Nature biotechnology
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...

Exposure to polydopamine nanoparticles induces neurotoxicity in the developing zebrafish.

NanoImpact
Currently, the potential applications of polydopamine (PDA) nanoparticles in the biomedical field are being extensively studied, such as cell internalization, biocompatible surface modification, biological imaging, nano-drug delivery, cancer diagnosi...

Weakly supervised underwater fish segmentation using affinity LCFCN.

Scientific reports
Estimating fish body measurements like length, width, and mass has received considerable research due to its potential in boosting productivity in marine and aquaculture applications. Some methods are based on manual collection of these measurements ...

Cross-Modality Interaction Network for Equine Activity Recognition Using Imbalanced Multi-Modal Data.

Sensors (Basel, Switzerland)
With the recent advances in deep learning, wearable sensors have increasingly been used in automated animal activity recognition. However, there are two major challenges in improving recognition performance-multi-modal feature fusion and imbalanced d...

Closing the Performance Gap between Siamese Networks for Dissimilarity Image Classification and Convolutional Neural Networks.

Sensors (Basel, Switzerland)
In this paper, we examine two strategies for boosting the performance of ensembles of Siamese networks (SNNs) for image classification using two loss functions (Triplet and Binary Cross Entropy) and two methods for building the dissimilarity spaces (...