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) is a widely used imaging technique to assess brain
tumor. Accurately segmenting brain tumor from MR images is the key to clinical diagnostics …

Glioma is the most common primary central nervous system tumor, accounting for about half
of all intracranial primary tumors. As a non-invasive examination method, MRI has an …

Medical data refers to health-related information associated with regular patient care or as
part of a clinical trial program. There are many categories of such data, such as clinical …

As a highly malignant tumor, the incidence and mortality of glioma are not optimistic.
Predicting the survival time of patients with glioma by extracting the feature information from …

An artificial intelligence (AI) model's performance is strongly influenced by the input features.
Therefore, it is vital to find the optimal feature set. It is more crucial for the survival prediction …

The most common and aggressive malignant brain tumor in adults is glioma, which leads to
short life expectancy. A reliable and efficient automatic segmentation method is beneficial for …

Glioma, a malignant brain tumor, requires immediate treatment to improve the survival of
patients. The heterogeneous nature of Glioma makes the segmentation difficult, especially …

The performance of deep learning-based methods depends mainly on the availability of
large-scale labeled learning data. However, obtaining precisely annotated examples is …