AIMC Topic: Humans

Clear Filters Showing 52551 to 52560 of 95995 articles

A deep learning system for automated, multi-modality 2D segmentation of vertebral bodies and intervertebral discs.

Bone
PURPOSE: Fractures in vertebral bodies are among the most common complications of osteoporosis and other bone diseases. However, studies that aim to predict future fractures and assess general spine health must manually delineate vertebral bodies and...

Machine learning for detection of interictal epileptiform discharges.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
The electroencephalogram (EEG) is a fundamental tool in the diagnosis and classification of epilepsy. In particular, Interictal Epileptiform Discharges (IEDs) reflect an increased likelihood of seizures and are routinely assessed by visual analysis o...

Deep learning model for distinguishing novel coronavirus from other chest related infections in X-ray images.

Computers in biology and medicine
Novel Coronavirus is deadly for humans and animals. The ease of its dispersion, coupled with its tremendous capability for ailment and death in infected people, makes it a risk to society. The chest X-ray is conventional but hard to interpret radiogr...

Multimodal super-resolved q-space deep learning.

Medical image analysis
Super-resolvedq-space deep learning (SR-q-DL) has been developed to estimate high-resolution (HR) tissue microstructure maps from low-quality diffusion magnetic resonance imaging (dMRI) scans acquired with a reduced number of diffusion gradients and ...

Brain graph super-resolution using adversarial graph neural network with application to functional brain connectivity.

Medical image analysis
Brain image analysis has advanced substantially in recent years with the proliferation of neuroimaging datasets acquired at different resolutions. While research on brain image super-resolution has undergone a rapid development in the recent years, b...

An integrated deep learning model for motor intention recognition of multi-class EEG Signals in upper limb amputees.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Recognition of motor intention based on electroencephalogram (EEG) signals has attracted considerable research interest in the field of pattern recognition due to its notable application of non-muscular communication and con...

SP rTaTME: initial clinical experience with single-port robotic transanal total mesorectal excision (SP rTaTME).

Techniques in coloproctology
BACKGROUND: The technical difficulty and steep learning curve of transanal total mesorectal excision (taTME) has limited widespread adoption. The single-port (SP) daVinci robot is designed to facilitate single-incision and natural-orifice translumina...

Towards markerless surgical tool and hand pose estimation.

International journal of computer assisted radiology and surgery
PURPOSE:  : Tracking of tools and surgical activity is becoming more and more important in the context of computer assisted surgery. In this work, we present a data generation framework, dataset and baseline methods to facilitate further research in ...