HCT-Net: hybrid CNN-transformer network with multi-scale feature aggregation and progressive decode for medical image segmentation

Key Points

• The hybrid CNN-transformer network significantly enhances image segmentation accuracy, improving detection of tumors and anomalies.
• The method integrates multi-scale feature aggregation, yielding higher precision compared to traditional models.
• Development utilized a series of medical images, leveraging convolutional neural networks and transformers effectively.
• The findings support the use of advanced neural networks for improving medical image analysis, urging further exploration in clinical settings.