I$^3$Net: Inter-Intra-slice Interpolation Network for Medical Slice Synthesis
<|reference_start|>I$^3$Net: Inter-Intra-slice Interpolation Network for Medical Slice Synthesis: Medical imaging is limited by acquisition time and scanning equipment. CT and MR volumes, reconstructed with thicker slices, are anisotropic with high in-plane resolution and low through-plane resolution. We reveal an intriguing phenomenon that due to the mentioned nature of data, performing slice-wise interpolation from the axial view can yield greater benefits than performing super-resolution from other views. Based on this observation, we propose an Inter-Intra-slice Interpolation Network (I$^3$Net), which fully explores information from high in-plane resolution and compensates for low through-plane resolution. The through-plane branch supplements the limited information contained in low through-plane resolution from high in-plane resolution and enables continual and diverse feature learning. In-plane branch transforms features to the frequency domain and enforces an equal learning opportunity for all frequency bands in a global context learning paradigm. We further propose a cross-view block to take advantage of the information from all three views online. Extensive experiments on two public datasets demonstrate the effectiveness of I$^3$Net, and noticeably outperforms state-of-the-art super-resolution, video frame interpolation and slice interpolation methods by a large margin. We achieve 43.90dB in PSNR, with at least 1.14dB improvement under the upscale factor of $\times$2 on MSD dataset with faster inference. Code is available at https://github.com/DeepMed-Lab-ECNU/Medical-Image-Reconstruction.<|reference_end|>
@article{song2024i$^3$net:,
    title={I$^3$Net: Inter-Intra-slice Interpolation Network for Medical Slice
  Synthesis},
    author={Haofei Song, Xintian Mao, Jing Yu, Qingli Li, Yan Wang},
    journal={arXiv preprint arXiv:2405.02857},
    year={2024},
    doi={10.1109/TMI.2024.3394033},
    archivePrefix={arXiv},
    eprint={2405.02857},
    primaryClass={eess.IV cs.CV}
}