MRI-based medical image analysis for brain tumor studies is gaining attention in recent
times due to an increased need for efficient and objective evaluation of large amounts of …

The successful early diagnosis of brain tumors plays a major role in improving the treatment
outcomes and thus improving patient survival. Manually evaluating the numerous magnetic …

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) …

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 …

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 …

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 …

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) …

Image segmentation is one of the most important tasks in medical image analysis and is
often the first and the most critical step in many clinical applications. In brain MRI analysis …

The central role of MRI in neuro-oncology is undisputed. The technique is used, both in
clinical practice and in clinical trials, to diagnose and monitor disease activity, support …

Brain tumor is the growth of abnormal cells in the brain and ranges from noncancerous
(benign) to malignant. Glioblastoma (GBM) is the most aggressive type of brain tumor, rising …