Enhanced Brain Tumor Segmentation and Classification Based on Quantum-Classical Attention-Guided Hybrid Framework with Zebra Optimization Algorithm

Key Points

• Enhanced brain tumor segmentation accuracy achieved through a novel attention-guided hybrid framework.
• Using a zebra optimization algorithm, the model outperforms traditional methods in classification tasks.
• The analysis incorporates both quantum and classical processing techniques to improve outcomes.
• Findings support further development of advanced computational models for medical imaging applications.