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Deep learning methodology for predicting time history of head angular kinematics from simulated crash videos.

Scientific reports
Head kinematics information is important as it is used to measure brain injury risk. Currently, head kinematics are measured using wearable devices or instrumentation mounted on the head. This paper evaluates the deep learning approach in predicting ...

Automatic measurement of fetal head circumference using a novel GCN-assisted deep convolutional network.

Computers in biology and medicine
The growth of the fetus can be effectively monitored by measuring the fetal head circumference (HC) in ultrasound images. Moreover, it is the key to assessing the fetus's health. Ultrasound fetal head image boundary is blurred. The ultrasound sound s...

SLEAP: A deep learning system for multi-animal pose tracking.

Nature methods
The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation in tools to quantify natural animal behavior. While advances in deep learning and computer vision have enabled markerless pose estimatio...

Deep Gaussian processes for multiple instance learning: Application to CT intracranial hemorrhage detection.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Intracranial hemorrhage (ICH) is a life-threatening emergency that can lead to brain damage or death, with high rates of mortality and morbidity. The fast and accurate detection of ICH is important for the patient to get an ...

Convolutional mesh autoencoders for the 3-dimensional identification of FGFR-related craniosynostosis.

Scientific reports
Clinical diagnosis of craniofacial anomalies requires expert knowledge. Recent studies have shown that artificial intelligence (AI) based facial analysis can match the diagnostic capabilities of expert clinicians in syndrome identification. In genera...

Effect of head motion-induced artefacts on the reliability of deep learning-based whole-brain segmentation.

Scientific reports
Due to their robustness and speed, recently developed deep learning-based methods have the potential to provide a faster and hence more scalable alternative to more conventional neuroimaging analysis pipelines in terms of whole-brain segmentation bas...

Research on Real-Time Face Key Point Detection Algorithm Based on Attention Mechanism.

Computational intelligence and neuroscience
The existing face detection methods were affected by the network model structure used. Most of the face recognition methods had low recognition rate of face key point features due to many parameters and large amount of calculation. In order to improv...

A stroke detection and discrimination framework using broadband microwave scattering on stochastic models with deep learning.

Scientific reports
Stroke poses an immense public health burden and remains among the primary causes of death and disability worldwide. Emergent therapy is often precluded by late or indeterminate times of onset before initial clinical presentation. Rapid, mobile, safe...

Face Manipulation Detection Based on Supervised Multi-Feature Fusion Attention Network.

Sensors (Basel, Switzerland)
Nowadays, faces in videos can be easily replaced with the development of deep learning, and these manipulated videos are realistic and cannot be distinguished by human eyes. Some people maliciously use the technology to attack others, especially cele...

Estimating Effective Connectivity by Recurrent Generative Adversarial Networks.

IEEE transactions on medical imaging
Estimating effective connectivity from functional magnetic resonance imaging (fMRI) time series data has become a very hot topic in neuroinformatics and brain informatics. However, it is hard for the current methods to accurately estimate the effecti...