This paper provides a comprehensive review of deep learning models for ischemic stroke
lesion segmentation in medical images. Ischemic stroke is a severe neurological disease …

Accurate segmentation of chronic stroke lesions from mono‐spectral magnetic resonance
imaging scans (eg, T1‐weighted images) is a difficult task due to the arbitrary shape …

Brain stroke, or a cerebrovascular accident, is a devastating medical condition that disrupts
the blood supply to the brain, depriving it of oxygen and nutrients. Each year, according to …

Brain-behaviour relationships are complex. For instance, one might know a brain region's
function (s) but still be unable to accurately predict deficit type or severity after damage to …

Navigating autonomous vehicles efficiently across unstructured and off-road terrains
remains a formidable challenge, often requiring intricate mapping or multi-step pipelines …

Background: Glomerular lesions reflect the onset and progression of renal disease.
Pathological diagnoses are widely regarded as the definitive method for recognizing these …

The potential benefit of introducing AI to stroke, in imaging and elsewhere, is now
unquestionable, but the optimal approach–and the path to real-world application–remain …

Medical image labeling requires specialized knowledge; hence, the solution to the
challenge of medical image classification lies in efficiently utilizing the few labeled samples …

The efficient navigation of autonomous vehicles across rugged and unstructured terrains
remains a significant challenge. Most existing research in this area emphasizes the need for …

Background: Stroke is a leading cause of morbidity and mortality worldwide. Accurate
segmentation of sub-acute and chronic stroke lesions using MRI is crucial for assessing …