AIMC Topic: Automation

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Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.

Medical physics
PURPOSE: Intensity modulated radiation therapy (IMRT) is commonly employed for treating head and neck (H&N) cancer with uniform tumor dose and conformal critical organ sparing. Accurate delineation of organs-at-risk (OARs) on H&N CT images is thus es...

A Scene Recognition and Semantic Analysis Approach to Unhealthy Sitting Posture Detection during Screen-Reading.

Sensors (Basel, Switzerland)
Behavior analysis through posture recognition is an essential research in robotic systems. Sitting with unhealthy sitting posture for a long time seriously harms human health and may even lead to lumbar disease, cervical disease and myopia. Automatic...

Automated cardiovascular magnetic resonance image analysis with fully convolutional networks.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction ...

EEG-Based Automatic Sleep Staging Using Ontology and Weighting Feature Analysis.

Computational and mathematical methods in medicine
Sleep staging is considered as an effective indicator for auxiliary diagnosis of sleep diseases and related psychiatric diseases, so it attracts a lot of attention from sleep researchers. Nevertheless, sleep staging based on visual inspection of trad...

Automated retinopathy of prematurity screening using deep neural networks.

EBioMedicine
BACKGROUND: Retinopathy of prematurity (ROP) is the leading cause of childhood blindness worldwide. Automated ROP detection system is urgent and it appears to be a safe, reliable, and cost-effective complement to human experts.

Quiet sleep detection in preterm infants using deep convolutional neural networks.

Journal of neural engineering
OBJECTIVE: Neonates spend most of their time asleep. Sleep of preterm infants evolves rapidly throughout maturation and plays an important role in brain development. Since visual labelling of the sleep stages is a time consuming task, automated analy...

Convolutional neural networks automate detection for tracking of submicron-scale particles in 2D and 3D.

Proceedings of the National Academy of Sciences of the United States of America
Particle tracking is a powerful biophysical tool that requires conversion of large video files into position time series, i.e., traces of the species of interest for data analysis. Current tracking methods, based on a limited set of input parameters ...

Automatic Classification of Gait Impairments Using a Markerless 2D Video-Based System.

Sensors (Basel, Switzerland)
Systemic disorders affecting an individual can cause gait impairments. Successful acquisition and evaluation of features representing such impairments make it possible to estimate the severity of those disorders, which is important information for mo...

Robotic microplate voltammetry for real-time hydrogel drug release testing.

Analytica chimica acta
Robotic square wave voltammetry (SVW) in 24-well microtiter plates has been developed as a reliable non-manual procedure for quantifying drug release from pharmaceutical hydrogels. The assay was established using 1% agarose disks containing Paracetam...