In this paper, we demonstrate the feasibility and performance of deep residual neural
networks for volumetric segmentation of irreversibly damaged brain tissue lesions on T1 …

The principle restorative step in the treatment of ischemic stroke depends on how fast the
lesion is delineated from the Magnetic Resonance Imaging (MRI) images. This will serve as …

Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of
stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would …

Ischemic stroke lesion and white matter hyperintensity (WMH) lesion appear as regions of
abnormally signal intensity on magnetic resonance image (MRI) sequences. Ischemic stroke …

The first and foremost step in the diagnosis of ischemic stroke is the delineation of the lesion
from radiological images for effective treatment planning. Manual delineation of the lesion by …

We present our 11-layers deep, double-pathway, 3D Convolutional Neural Network,
developed for the segmentation of brain lesions. The developed system segments pathology …

Lesion studies are crucial in establishing brain-behavior relationships, and accurately
segmenting the lesion represents the first step in achieving this. Manual lesion segmentation …

Correct segmentation of stroke lesions from magnetic resonance imaging (MRI) is crucial for
neurologists and patients. However, manual segmentation relies on expert experience and …

The accurate segmentation of brain stroke lesions in medical images are critical for early
diagnosis, treatment planning, and monitoring of stroke patients. In recent years, deep …

The patient with ischemic stroke can benefit most from the earliest possible definitive
diagnosis. While a quantitative evaluation of the stroke lesions on the magnetic resonance …