
We open source a dataset RPLHR-CT for the paper "RPLHR-CT Dataset and Transformer Baseline for Volumetric Super-Resolution from CT Scans". We also release the code and datasets at https://github.com/smilenaxx/RPLHR-CT. The RPLHR-CT dataset contains 250 cases (100 cases for training, 50 cases for validation, 100 cases for testing). If you have any questions about the dataset or the code, you can email ypengxin@infervision.com. It would be high appreciated if you can cite our paper when using our dataset: "Yu P, Zhang H, Kang H, et al. RPLHR-CT dataset and transformer baseline for volumetric super-resolution from CT scans[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer Nature Switzerland, 2022: 344-353."
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
