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Automated comprehensive Adolescent Idiopathic Scoliosis assessment using MVC-Net.

Medical image analysis
Automated quantitative estimation of spinal curvature is an important task for the ongoing evaluation and treatment planning of Adolescent Idiopathic Scoliosis (AIS). It solves the widely accepted disadvantage of manual Cobb angle measurement (time-c...

Effect of forward-directed aiding force on gait mechanics in healthy young adults while walking faster.

Gait & posture
BACKGROUND: Forces can be applied to people while they are walking on a treadmill in different ways that aid individuals to walk at faster walking speeds with potentially less effort. Forward-directed aiding forces (FAF) are a special class of aiding...

Assessment of the generalization of learned image reconstruction and the potential for transfer learning.

Magnetic resonance in medicine
PURPOSE: Although deep learning has shown great promise for MR image reconstruction, an open question regarding the success of this approach is the robustness in the case of deviations between training and test data. The goal of this study is to asse...

Deep convolutional neural network for segmentation of knee joint anatomy.

Magnetic resonance in medicine
PURPOSE: To describe and evaluate a new segmentation method using deep convolutional neural network (CNN), 3D fully connected conditional random field (CRF), and 3D simplex deformable modeling to improve the efficiency and accuracy of knee joint tiss...

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

IEEE transactions on medical imaging
Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish diagnosis. The automation of the corresponding tasks has thus been th...

The temporal evolution of conceptual object representations revealed through models of behavior, semantics and deep neural networks.

NeuroImage
Visual object representations are commonly thought to emerge rapidly, yet it has remained unclear to what extent early brain responses reflect purely low-level visual features of these objects and how strongly those features contribute to later categ...

A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.

Computers in biology and medicine
The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an imminent seizure. In this work, Long Short-Term Memory (LSTM) networks are introduced in epileptic sei...

Encoding of Articulatory Kinematic Trajectories in Human Speech Sensorimotor Cortex.

Neuron
When speaking, we dynamically coordinate movements of our jaw, tongue, lips, and larynx. To investigate the neural mechanisms underlying articulation, we used direct cortical recordings from human sensorimotor cortex while participants spoke natural ...

Modeling Dengue vector population using remotely sensed data and machine learning.

Acta tropica
Mosquitoes are vectors of many human diseases. In particular, Aedes ægypti (Linnaeus) is the main vector for Chikungunya, Dengue, and Zika viruses in Latin America and it represents a global threat. Public health policies that aim at combating this v...