Approche multi-axes basée deep learning pour la segmentation 3D du diaphragme

Key Points

• This approach enhances 3D segmentation of the diaphragm, improving image quality and precision.
• Key evidence shows an increase in segmentation accuracy by 30% compared to traditional methods.
• Analysis using advanced neural networks for 3D segmentation emphasizes robust performance dynamics.
• Implication suggests that improved segmentation can lead to better diagnostics and treatment planning in clinical practice.