AIMC Topic: Automation

Clear Filters Showing 461 to 470 of 967 articles

CAST: A multi-scale convolutional neural network based automated hippocampal subfield segmentation toolbox.

NeuroImage
In this study, we developed a multi-scale Convolutional neural network based Automated hippocampal subfield Segmentation Toolbox (CAST) for automated segmentation of hippocampal subfields. Although training CAST required approximately three days on a...

Automated computer-assisted detection system for cerebral aneurysms in time-of-flight magnetic resonance angiography using fully convolutional network.

Biomedical engineering online
BACKGROUND: As the rupture of cerebral aneurysm may lead to fatal results, early detection of unruptured aneurysms may save lives. At present, the contrast-unenhanced time-of-flight magnetic resonance angiography is one of the most commonly used meth...

Beyond safety drivers: Applying air traffic control principles to support the deployment of driverless vehicles.

PloS one
By adopting and extending lessons from the air traffic control system, we argue that a nationwide remote monitoring system for driverless vehicles could increase safety dramatically, speed these vehicles' deployment, and provide employment. It is bec...

CytoCensus, mapping cell identity and division in tissues and organs using machine learning.

eLife
A major challenge in cell and developmental biology is the automated identification and quantitation of cells in complex multilayered tissues. We developed CytoCensus: an easily deployed implementation of supervised machine learning that extends conv...

Automated fibroglandular tissue segmentation in breast MRI using generative adversarial networks.

Physics in medicine and biology
Fibroglandular tissue (FGT) segmentation is a crucial step for quantitative analysis of background parenchymal enhancement (BPE) in magnetic resonance imaging (MRI), which is useful for breast cancer risk assessment. In this study, we develop an auto...

An Automated Segmentation Pipeline for Intratumoural Regions in Animal Xenografts Using Machine Learning and Saturation Transfer MRI.

Scientific reports
Saturation transfer MRI can be useful in the characterization of different tumour types. It is sensitive to tumour metabolism, microstructure, and microenvironment. This study aimed to use saturation transfer to differentiate between intratumoural re...

Automatic Triage of 12-Lead ECGs Using Deep Convolutional Neural Networks.

Journal of the American Heart Association
BACKGROUND The correct interpretation of the ECG is pivotal for the accurate diagnosis of many cardiac abnormalities, and conventional computerized interpretation has not been able to reach physician-level accuracy in detecting (acute) cardiac abnorm...

Deep learning enables automated localization of the metastatic lymph node for thyroid cancer on I post-ablation whole-body planar scans.

Scientific reports
The accurate detection of radioactive iodine-avid lymph node (LN) metastasis on I post-ablation whole-body planar scans (RxWBSs) is important in tracking the progression of the metastatic lymph nodes (mLNs) of patients with papillary thyroid cancer (...

Automatic snoring sounds detection from sleep sounds based on deep learning.

Physical and engineering sciences in medicine
Snoring is a typical characteristic of obstructive sleep apnea hypopnea syndrome (OSAHS) and can be used for its diagnosis. The purpose of this paper is to develop an automatic snoring detection algorithm for classifying snore and non-snore sound seg...

BPBSAM: Body part-specific burn severity assessment model.

Burns : journal of the International Society for Burn Injuries
BACKGROUND AND OBJECTIVE: Burns are a serious health problem leading to several thousand deaths annually, and despite the growth of science and technology, automated burns diagnosis still remains a major challenge. Researchers have been exploring vis...