Recent advances and future perspectives of machine learning techniques offer promising
applications in medical imaging. Machine learning has the potential to improve different …

Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining
increasing interest and is being incorporated into many fields, including medicine. Stroke …

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification
of lesion burden and accurate image processing. Current automated lesion segmentation …

Stroke is the leading cause of adult disability worldwide, with up to two-thirds of individuals
experiencing long-term disabilities. Large-scale neuroimaging studies have shown promise …

Magnetic resonance imaging (MRI) is effectively used for accurate diagnosis of acute
ischemic stroke. This paper presents an automated method based on computer aided …

Background: Authors have been advocating the research ideology that a computer-aided
diagnosis (CAD) system trained using lots of patient data and physiological signals and …

Lesion‐symptom map** has become a cornerstone of neuroscience research seeking to
localize cognitive function in the brain by examining the sequelae of brain lesions. Recently …

Lesion to symptom map** (LSM) is a crucial tool for understanding the causality of brain-
behavior relationships. The analyses are typically performed by applying statistical methods …

Performance of models highly depend not only on the used algorithm but also the data set it
was applied to. This makes the comparison of newly developed tools to previously …

Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …