In biomedical image analysis, information about the location and appearance of tumors and
lesions is indispensable to aid doctors in treating and identifying the severity of diseases …

Background Magnetic resonance image (MRI) brain tumor segmentation is crucial and
important in the medical field, which can help in diagnosis and prognosis, overall growth …

Background Automatic segmentation of brain tumours using deep learning algorithms is
currently one of the research hotspots in the medical image segmentation field. An improved …

The state-of-the-art works for the segmentation of brain tumor using the images acquired by
Magnetic Resonance Imaging (MRI) with their performances are analyzed in this …

Magnetic Resonance Imaging (MRI) is an important diagnostic technique for brain tumors
due to its ability to generate images without tissue damage or skull artifacts. Therefore, MRI …

The primary strategy for mitigating lost productivity entails promptly, accurately, and
efficiently detecting plant pests. Although detection by humans can be useful in detecting …

Convolutional network models have been widely used in image segmentation. However,
there are many types of boundary contour features in medical images which seriously affect …

Brain tumor segmentation using MRI remains a challenging task due to the high incidence
and complexity of gliomas. The irregular variations in tumor location, size, shape, and …

Brain tumor segmentation is an essential task for medical diagnosis and treatment planning.
Multi-modal MRI provides complementary information that is essential for accurate …

Brain tumors can be a life-threatening condition, and early detection is crucial for effective
treatment. Magnetic resonance imaging (MRI) is a valuable appliance for identifying the …