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) …

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 …

Brain tumor is one of the most life-threatening diseases and hence its detection should be
fast and accurate. This can be achieved by the execution of automated tumor detection …

Computer ministered analysis is needed to diagnose nervous system diseases. Among the
various human brain disorders ischemic stroke dominates and acts as the leading cause of …

This paper proposes a novel brain tumor segmentation algorithm that uses Active Contour
Model and Fuzzy-C-Means optimization. In Active Contour model, the initial Contour …

Image segmentation, ie, dividing an image into its constituent's regions, is a decisive phase
in plentiful medical imaging studies to extract meaningful information such as shape …

Brain tumor segmentation plays a vital role in surgical, treatment planning and follow-up
studies. The noninvasive nature, better soft tissue contrast, and no ionizing radiation makes …

The formation of abnormal cells within the brain is termed as brain tumor. Brain tumors can
be benign or cancerous. Brain being the major organ of the body controls every activity we …

Biomedical images are the core of medical science. Magnetic Resonance Imaging (MRI)
scans produce detailed images of the internal structure of human brain and other parts of the …

The detection of brain tumor is one of the most challenging tasks in the field of medical
image processing, since brain images are very complicated and tumors can be analyzed …