Brain tumor segmentation has the most important significance in tumor diagnose, analysis,
and treatment. Magnetic resonance imaging (MRI) provides rich and valuable information for …

In this paper, we propose a novel method based on the fully convolutional network for brain
tumor segmentation from magnetic resonance imaging. The proposed method divides the …

Brain tumor segmentation plays an important role in clinical diagnosis for neurologists.
Different imaging modalities have been used to diagnose and segment brain tumor. Among …

Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis.
According to deep learning model, a novel brain tumor segmentation method is developed …

Accurate segmentation of brain tumors from magnetic resonance imaging (MRI) images is
still a challenging task for many applications in the medical domain. To gain a better …

Background Glioma is the most common brain malignant tumor, with a high morbidity rate
and a mortality rate of more than three percent, which seriously endangers human health …

Purpose Accurate outline of tumor targets is critical to a high quality radiotherapy plan.
Manual segmentation is of great workload and has a strong artificial subjectivity. Using deep …

The human brain is the most vital and complicated organ in the body, restricting the entire
organism. Correctly diagnosing a brain tumor is difficult due to its complexity. An …

Segmenting brain tumors is crucial for improving diagnosis, prognosis, and therapy options.
Brain tumors treatment must begin right away, because identifying brain tumors manually is …

Background The determination of area tumor presents the chief challenge in brain tumor
therapy and assessment. Without ionizing radiation, the medical Magnetic Resonance …