Stroke is an emergency in which delays in treatment can lead to significant loss of
neurological function and be fatal. Technologies that increase the speed and accuracy of …

Intracerebral hemorrhage (ICH) is the most common type of hemorrhagic stroke which
occurs due to ruptures of weakened blood vessel in brain tissue. It is a serious medical …

Automatic intracranial hemorrhage segmentation in 3D non-contrast head CT (NCCT) scans
is significant in clinical practice. Existing hemorrhage segmentation methods usually ignores …

With the recent development of deep learning, the classification and segmentation tasks of
computer-aided diagnosis (CAD) using non-contrast head computed tomography (NCCT) …

Intracranial hemorrhage (ICH) is a serious medical condition that necessitates a prompt and
exhaustive medical diagnosis. This paper presents a multi-label ICH classification issue with …

Imaging anisotropy poses a critical challenge in applying deep learning models to 3D
medical image analysis. Anisotropy downgrades model performance, especially when slice …

This study evaluated deep learning algorithms for semantic segmentation and quantification
of intracerebral hemorrhage (ICH), perihematomal edema (PHE), and intraventricular …

Stroke”. Computed tomographic (CT) images play a crucial role in identifying hemorrhagic
strokes. It also helps in understanding the impact of damage caused in the brain cells more …

Brain hemorrhage refers to a potentially fatal medical disorder that affects millions of
individuals. The percentage of patients who survive can be significantly raised with the …

Intracranial Hemorrhage (ICH) refers to bleeding inside the brain or skull and is considered
a life-threatening condition as the accumulation of blood can lead to increased intracranial …