The introduction of quantitative image analysis has given rise to fields such as radiomics
which have been used to predict clinical sequelae. One growing area of interest for analysis …

Image denoising and segmentation are required to use in digital image processing. For
researchers' point of view, still, these two methods are challenging task in medical images …

Brain tumor segmentation aims to separate the different tumor tissues such as active cells,
necrotic core, and edema from normal brain tissues of White Matter (WM), Gray Matter (GM) …

The aim of this study was to computationally model, in an unsupervised manner, a manifold
of symmetry variations in normal brains, such that the learned manifold can be used to …

Over the past few years, a tremendous change has occurred in computer‐aided diagnosis
(CAD) technology. The evolution of numerous medical imaging techniques has enhanced …

An automatic brain tumor segmentation method based on texture feature and kernel sparse
coding from FLAIR (fluid attenuated inversion recovery) contrast-enhanced MRIs (magnetic …

Abstract Purpose Structural Magnetic Resonance Imaging (MRI) of the brain is an effective
way to study its internal structure. Identifying and classifying brain malignancies is a difficult …

Automatic segmentation of brain tumour is the process of separating abnormal tissues from
normal tissues, such as white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) …

Computer‐aided diagnosis and treatment of multimodal magnetic resonance imaging (MRI)
brain tumor image segmentation has always been a hot and significant topic in the field of …

Background. Prognosis of long-term motor outcome of acute stroke patients with severe
motor impairment is difficult to determine. Objective. Our primary goal was to evaluate the …