Introduction In neurological diagnostics, accurate detection and segmentation of brain
lesions is crucial. Identifying these lesions is challenging due to its complex morphology …

A deep convolutional neural network (CNN) achieves remarkable performance for medical
image analysis. UNet is the primary source in the performance of 3D CNN architectures for …

Brain tumors are among the deadliest forms of cancer, characterized by abnormal
proliferation of brain cells. While early identification of brain tumors can greatly aid in their …

MR images (MRIs) accurate segmentation of brain lesions is important for improving cancer
diagnosis, surgical planning, and prediction of outcome. However, manual and accurate …

Accurate brain tumor segmentation plays an essential role in the diagnosis process.
However, there are challenges due to the variety of tumors in low contrast, morphology …

Medical image segmentation is a crucial topic in medical image processing. Accurately
segmenting brain tumor regions from multimodal MRI scans is essential for clinical …

In MRI images, the brain tumor area varies greatly between individuals, and only relying on
the judgment of clinicians is prone to misdiagnosis and misjudgment. Consequently, utilizing …

In recent years, the increasing incidence of morbidity of brain stroke has made fast and
accurate segmentation of lesion areas from brain MRI images important. With the …

Accurate segmentation of brain tumor from magnetic resonance images (MRIs) is crucial for
clinical treatment decision and surgical planning. Due to the large diversity of the tumors and …

Glioblastoma is a highly aggressive and malignant brain tumor type that requires early
diagnosis and prompt intervention. Due to its heterogeneity in appearance, developing …