The abnormal growth of malignant or nonmalignant tissues in the brain causes long-term
damage to the brain. Magnetic resonance imaging (MRI) is one of the most common …

A brain tumor is one of the fatal cancer types which causes abnormal growth of brain cells.
Earlier diagnosis of a brain tumor can play a vital role in its treatment; however, manual …

Background Image segmentation is an essential step in the analysis and subsequent
characterisation of brain tumours through magnetic resonance imaging. In the literature …

Multimodal glioma images provide different features of tumor boundaries based on magnetic
resonance imaging (MRI), where multimodal features are often challenging to extract for …

Objective Glioblastoma multiforme (GBM) is a grade IV brain tumour with very low life
expectancy. Physicians and oncologists urgently require automated techniques in clinics for …

Cancer of the brain is deadly and requires careful surgical segmentation. The brain tumors
were segmented using U-Net using a Convolutional Neural Network (CNN). When looking …

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 …

Radiomics-guided prediction of overall survival (OS) in brain gliomas is seen as a significant
problem in Neuro-oncology. The ultimate goal is to develop a robust MRI-based approach …

The symmetrical segmentation of brain tumor images is crucial for both clinical diagnosis
and computer-aided prognosis. Traditional manual methods are not only asymmetrical in …

Nakagami distribution and related imaging methods are very efficient in diagnostic
ultrasonography for visualization and characterization of tissues for years. Abnormalities in …