AIMC Topic: Deep Learning

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Evidence that the Kennedy and polyamine pathways are dysregulated in human brain in cases of dementia with Lewy bodies.

Brain research
Disruptions of brain metabolism are considered integral to the pathogenesis of dementia, but thus far little is known of how dementia with Lewy bodies (DLB) impacts the brain metabolome. DLB is less well known than other neurodegenerative diseases su...

DLPNet: A deep manifold network for feature extraction of hyperspectral imagery.

Neural networks : the official journal of the International Neural Network Society
Deep learning has received increasing attention in recent years and it has been successfully applied for feature extraction (FE) of hyperspectral images. However, most deep learning methods fail to explore the manifold structure in hyperspectral imag...

Response score of deep learning for out-of-distribution sample detection of medical images.

Journal of biomedical informatics
Deep learning Convolutional Neural Networks have achieved remarkable performance in a variety of classification tasks. The data-driven nature of deep learning indicates that a model behaves in response to the data used to train the model, and the qua...

Encoder-decoder CNN models for automatic tracking of tongue contours in real-time ultrasound data.

Methods (San Diego, Calif.)
One application of medical ultrasound imaging is to visualize and characterize human tongue shape and motion in real-time to study healthy or impaired speech production. Due to the low-contrast characteristic and noisy nature of ultrasound images, it...

WGAN domain adaptation for the joint optic disc-and-cup segmentation in fundus images.

International journal of computer assisted radiology and surgery
PURPOSE: The cup-to-disc ratio (CDR), a clinical metric of the relative size of the optic cup to the optic disc, is a key indicator of glaucoma, a chronic eye disease leading to loss of vision. CDR can be measured from fundus images through the segme...

Spatio-temporal deep learning methods for motion estimation using 4D OCT image data.

International journal of computer assisted radiology and surgery
PURPOSE: Localizing structures and estimating the motion of a specific target region are common problems for navigation during surgical interventions. Optical coherence tomography (OCT) is an imaging modality with a high spatial and temporal resoluti...

Recognition of Human Activities Using Depth Maps and the Viewpoint Feature Histogram Descriptor.

Sensors (Basel, Switzerland)
In this paper we propose a way of using depth maps transformed into 3D point clouds to classify human activities. The activities are described as time sequences of feature vectors based on the Viewpoint Feature Histogram descriptor (VFH) computed usi...

Estimating Lower Extremity Running Gait Kinematics with a Single Accelerometer: A Deep Learning Approach.

Sensors (Basel, Switzerland)
Abnormal running kinematics are associated with an increased incidence of lower extremity injuries among runners. Accurate and unobtrusive running kinematic measurement plays an important role in the detection of gait abnormalities and the prevention...

Distinguishing Obstructive Versus Central Apneas in Infrared Video of Sleep Using Deep Learning: Validation Study.

Journal of medical Internet research
BACKGROUND: Sleep apnea is a respiratory disorder characterized by an intermittent reduction (hypopnea) or cessation (apnea) of breathing during sleep. Depending on the presence of a breathing effort, sleep apnea is divided into obstructive sleep apn...

Deep Learning Automated Detection of Reticular Pseudodrusen from Fundus Autofluorescence Images or Color Fundus Photographs in AREDS2.

Ophthalmology
PURPOSE: To develop deep learning models for detecting reticular pseudodrusen (RPD) using fundus autofluorescence (FAF) images or, alternatively, color fundus photographs (CFP) in the context of age-related macular degeneration (AMD).