Performance analysis of CQ-CNN models across axial, coronal, sagittal, and combined 3-plane views.

Key evaluation metrics, including precision, F1-score, specificity, accuracy, and training time, are provided for models using both 2-qubit () and 3-qubit () configurations, where i represents experiments conducted on a specific dataset variation. Each metric is reported as the mean and standard deviation over multiple runs. The analysis also examines the impact of skull-stripping (denoted by ) on model performance and compares results based on whether the models were trained with single-plane (2D) or multi-plane (3D) images. Boldface numbers indicate the best performance. The symbol ↑ denotes that a higher value is better, while ↓ signifies that a lower value is better.