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) …

Brain tumor segmentation consists of separating the different tumor tissues (solid or active
tumor, edema, and necrosis) from normal brain tissues: gray matter (GM), white matter (WM) …

Inference of tumor and edema areas from brain magnetic resonance imaging (MRI) data
remains challenging owing to the complex structure of brain tumors, blurred boundaries, and …

Tumor segmentation from magnetic resonance imaging (MRI) data is an important but time
consuming manual task performed by medical experts. Automating this process is a …

Background Brain cancer is a destructive and life-threatening disease that imposes
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …

The precise segmentation of brain tumor images is a vital step towards accurate diagnosis
and effective treatment of brain tumors. Magnetic Resonance Imaging (MRI) can generate …

Magnetic Resonance Imaging (MRI) has commonly been used to detect and diagnose brain
disease and monitor treatment as non-invasive imaging technology. MRI produces three …

Medical image segmentation plays an important role in medical-imaging applications and
they provide a large amount of functional and anatomical information, which improve and …

Brain tumor analysis plays an important role in medical imaging applications and in
delivering a huge amount of anatomical and functional information, which increases and …

In the analysis of medical images, one of the challenging tasks is the recognition of brain
tumours via medical resonance images (MRIs). The diagnosis process is still tedious due to …