In recent years, there has been a burgeoning interest in the application of DNNs in tomography, notably in enhancing the quality of real-space reconstructed images generated from sinograms. Besides, some innovative applications even leverage supervised learning and generative models to automatically map from sinogram to real space . Despite certain bottlenecks such as handling large images and the computational cost of large networks, the promise of deep learning in this sphere is quite palpable.