Dee.rar

: The network utilizes patch-based training , which helps reduce the risk of overfitting to specific anatomical structures and improves the model's ability to generalize to different datasets.

: It is designed to remove ring and partial ring artifacts that often occur in CT scans due to detector imbalances. Dee.rar

If you are looking for the technical documentation or the PDF itself, you can find the detailed presentation from the on DeepRAR: A CNN-Based Approach for CT and CBCT Ring Artifact Reduction . : The network utilizes patch-based training , which

: Studies show it effectively improves image quality in both simulated and measured micro-CT data, often removing the need for manual parameter optimization or complex resampling. : Studies show it effectively improves image quality

: The research indicates that a 2.5D architecture yields the best results. This method utilizes information from adjacent image slices to better identify and remove artifacts compared to standard 2D approaches.

The specific "paper regarding Dee.rar" most likely refers to the research titled , which discusses techniques for improving image quality through deep learning. Key Aspects of DeepRAR