AIMC Topic: Humans

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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...

Leveraging spatial uncertainty for online error compensation in EMT.

International journal of computer assisted radiology and surgery
PURPOSE: Electromagnetic tracking (EMT) can potentially complement fluoroscopic navigation, reducing radiation exposure in a hybrid setting. Due to the susceptibility to external distortions, systematic error in EMT needs to be compensated algorithmi...

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...

Prediction of breast cancer proteins involved in immunotherapy, metastasis, and RNA-binding using molecular descriptors and artificial neural networks.

Scientific reports
Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental determinants are involved. Due to the complexity of BC, the predi...

Combining gene expression profiling and machine learning to diagnose B-cell non-Hodgkin lymphoma.

Blood cancer journal
Non-Hodgkin B-cell lymphomas (B-NHLs) are a highly heterogeneous group of mature B-cell malignancies. Their classification thus requires skillful evaluation by expert hematopathologists, but the risk of error remains higher in these tumors than in ma...

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...

Health status prediction for the elderly based on machine learning.

Archives of gerontology and geriatrics
Health and social care services are crucial to old people. The provision of services to the elderly with care needs requires more accurate predictions of the health status of the elderly to rationalize the allocation of the limited social care resour...