Intracranial hemorrhage (ICH) is an emergency and a potentially life-threatening condition.
Automated segmentation of ICH from head CT images can provide clinicians with volumetric …

This study presents a deep learning model for efficient intracranial hemorrhage (ICH)
detection and subtype classification on non-contrast head computed tomography (CT) …

Featured Application In the future, this method can help clinicians to diagnose the
approximate location of intracranial hemorrhage. Abstract Intracranial hemorrhage (ICH) is a …

Intracranial hemorrhage is an acute bleeding within the skull which can damage the brain
tissue and can eventually lead to disability or even death. It is a serious medical condition …

Head CT is one of the most commonly performed imaging studied in the Emergency
Department setting and Intracranial hemorrhage (ICH) is among the most critical and time …

Intracranial hemorrhages (ICHs) are life-threatening brain injures with a relatively high
incidence. In this paper, the automatic algorithm for the detection and classification of ICHs …

Timely diagnosis is crucial for the successful treatment of a serious medical condition like
brain hemorrhage. Deep learning algorithms have shown great promise in applications for …

ABSTRACT AIM: To present an early warning system (EWS) that employs a supervised
machine learning algorithm for the rapid detection of extra-axial hematomas (EAHs) in an …

Abstract Our Visual Analytics (VA) tool ScrutinAI supports human analysts to investigate
interactively model performance and data sets. Model performance depends on labeling …

Neural networks have shown great success in extracting geometric information from color
images. Especially, monocular depth estimation networks are increasingly reliable in real …