BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) is an important event that is
diagnosed on head NCCT. Increased NCCT utilization in busy hospitals may limit timely …

Background Highly accurate detection of intracranial hemorrhages (ICH) on head computed
tomography (HCT) scans can prove challenging at high-volume centers. This study aimed to …

Acute Intracranial hemorrhage (ICH) is a life-threatening disease that requires emergency
medical attention, which is routinely diagnosed using non-contrast head CT imaging. The …

Background Artificial intelligence applications have gained traction in the field of
cerebrovascular disease by assisting in the triage, classification, and prognostication of both …

Background Immediate and accurate detection of intracranial hemorrhages (ICHs) is
essential to provide a good clinical outcome for patients with ICH. Artificial intelligence has …

Purpose To analyze the implementation of deep learning software for the detection and
worklist prioritization of acute intracranial hemorrhage on non-contrast head CT (NCCT) in …

Purpose We evaluate the performance of a deep learning-based pipeline using a Dense U-
net architecture for detection of intracranial hemorrhage (ICH) in unenhanced head …

Purpose To present a method that automatically detects, subtypes, and locates acute or
subacute intracranial hemorrhage (ICH) on noncontrast CT (NCCT) head scans; generates …

Background Accurate measurement of hemorrhage volume is critical for both the prediction
of prognosis and the selection of appropriate clinical treatment after spontaneous …

Objectives To evaluate the performance of a novel three-dimensional (3D) joint
convolutional and recurrent neural network (CNN-RNN) for the detection of intracranial …