Pushing the limits of spatial resolution in clinical PCD‐CT using a dedicated high‐resolution convolutional neural network (HR‐CNN)

The spatial resolution of PCD-CT is not maximized in routine practice due to the large FOV and high noise levels at sharp kernels. The proposed HR-CNN denoising method, along with small pixel size, may allow the high spatial resolution toward the system limit to be implemented in practice, which is beneficial in the diagnosis of many diseases, including interstitial lung disease.