Uncertainty quantification (UQ) methods play a pivotal role in reducing the impact of
uncertainties during both optimization and decision making processes. They have been …

Data augmentation is a popular technique which helps improve generalization capabilities
of deep neural networks, and can be perceived as implicit regularization. It plays a pivotal …

Over the last decade, neural networks have reached almost every field of science and
become a crucial part of various real world applications. Due to the increasing spread …

Brain tumor classification is a very important and the most prominent step for assessing life‐
threatening abnormal tissues and providing an efficient treatment in patient recovery. To …

Gliomas are the most common primary brain malignancies, with different degrees of
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie …

Brain tumor segmentation technology plays a pivotal role in the process of diagnosis and
treatment of MRI brain tumors. It helps doctors to locate and measure tumors, as well as …

Nowadays, deep learning has achieved remarkable results in many computer vision related
tasks, among which the support of big data is essential. In this paper, we propose a full stage …

Automatic segmentation of brain tumors from medical images is important for clinical
assessment and treatment planning of brain tumors. Recent years have seen an increasing …

Research in the medical imaging field using deep learning approaches has become
progressively contingent. Scientific findings reveal that supervised deep learning methods' …

Reliable brain tumor segmentation is essential for accurate diagnosis and treatment
planning. Since manual segmentation of brain tumors is a highly time-consuming, expensive …