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Inter-Slice Resolution Improvement Using Convolutional Neural Network with Orbital Bone Edge-Aware in Facial CT Images.

Journal of digital imaging
The 3D modeling of orbital bones in facial CT images is essential to provide a customized implant for reconstructions of orbit and related structures during surgery. However, 3D models of the orbital bone show an aliasing effect and disconnected thin...

The contribution of object identity and configuration to scene representation in convolutional neural networks.

PloS one
Scene perception involves extracting the identities of the objects comprising a scene in conjunction with their configuration (the spatial layout of the objects in the scene). How object identity and configuration information is weighted during scene...

Automatic head computed tomography image noise quantification with deep learning.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Computed tomography (CT) image noise is usually determined by standard deviation (SD) of pixel values from uniform image regions. This study investigates how deep learning (DL) could be applied in head CT image noise estimation.

Automated soccer head impact exposure tracking using video and deep learning.

Scientific reports
Head impacts are highly prevalent in sports and there is a pressing need to investigate the potential link between head impact exposure and brain injury risk. Wearable impact sensors and manual video analysis have been utilized to collect impact expo...

Age Estimation of Faces in Videos Using Head Pose Estimation and Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Age estimation from human faces is an important yet challenging task in computer vision because of the large differences between physical age and apparent age. Due to the differences including races, genders, and other factors, the performance of a l...

Efficient fetal ultrasound image segmentation for automatic head circumference measurement using a lightweight deep convolutional neural network.

Medical physics
PURPOSE: Fetal head circumference (HC) is an important biometric parameter that can be used to assess fetal development in obstetric clinical practice. Most of the existing methods use deep neural network to accomplish the task of automatic fetal HC ...

AutoAtlas: Neural Network for 3D Unsupervised Partitioning and Representation Learning.

IEEE journal of biomedical and health informatics
We present a novel neural network architecture called AutoAtlas for fully unsupervised partitioning and representation learning of 3D brain Magnetic Resonance Imaging (MRI) volumes. AutoAtlas consists of two neural network components: one neural netw...

Machine learning and geometric morphometrics to predict obstructive sleep apnea from 3D craniofacial scans.

Sleep medicine
BACKGROUND: Obstructive sleep apnea (OSA) remains massively underdiagnosed, due to limited access to polysomnography (PSG), the highly complex gold standard for diagnosis. Performance scores in predicting OSA are evaluated for machine learning (ML) a...

Labeling Noncontrast Head CT Reports for Common Findings Using Natural Language Processing.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Prioritizing reading of noncontrast head CT examinations through an automated triage system may improve time to care for patients with acute neuroradiologic findings. We present a natural language-processing approach for label...

Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability.

Sensors (Basel, Switzerland)
In aerospace, marine, and other heavy industries, bearing fault diagnosis has been an essential part of improving machine life, reducing economic losses, and avoiding safety problems caused by machine bearing failures. Most existing bearing fault dia...