O-Net: a Brain Tumor Segmentation Architecture Based on U-Net Using Alternated Pooling

Key Points

• Effective brain tumor segmentation is achieved using the O-Net architecture with alternated pooling techniques,
• The segmentation process incorporates novel pooling methods, significantly improving resolution and accuracy,
• This observational analysis applies advanced segmentation algorithms to enhance neural imaging quality,
• Results may enable better clinical outcomes in tumor detection and treatment planning.