The exponential growth of deep learning networks has allowed us to tackle complex tasks,
even in fields as complicated as medicine. However, using these models requires a large …

More than half of brain tumors are malignant tumors, so there is a need for fast and accurate
segmentation of tumor regions in brain Magnetic Resonance Imaging (MRI) images …

Several techniques are used to detect brain tumors in the medical research field; however,
Magnetic Resonance Imaging (MRI) is still the most effective technique used by experts …

Brain tumors are highly hazardous, and precise automated segmentation of brain tumor
subregions has great importance and research significance on the diagnosis and treatment …

Brain tumor segmentation has been a challenging and popular research problem in the area
of medical imaging and computer-aided diagnosis. In the last few years, especially since …

The segmentation of magnetic resonance (MR) images is a crucial task for creating pseudo
computed tomography (CT) images which are used to achieve positron emission …

Brain tumor is one of the leading causes of cancer death. The high-grade brain tumors are
easier to recurrent even after standard treatment. Therefore, developing a method to predict …

The exponential growth of deep learning networks has enabled us to handle difficult tasks,
even in the complex field of medicine. Nevertheless, for these models to be extremely …

The paper aims at an enhanced deep learning-based brain tumor segmentation model of
MRI images. The input MRI images are pre-processed by the filtering and contrast …

Brain tumor is one of the most aggressive cancers in the world, accurate brain tumor
segmentation plays a critical role in clinical diagnosis and treatment planning. Although …