wtf is rddm?

This repository is the official code release for a research paper titled RDDM: A Residual-Driven Drifting Model for High-Fidelity Low-Dose CT Denoising. The README is very short and the project is openly marked as ongoing, which means most of the implementation has not been published yet. The topic of the paper, judging by the title, is medical imaging. CT stands for computed tomography, the cross-sectional X-ray imaging that hospitals use. Low-dose CT means scans done with less radiation, which is safer for the patient but produces noisier and grainier pictures. Denoising in this context is the process of cleaning that grainy output so the underlying structures are easier to see. RDDM, as named in the title, is described as a residual-driven drifting model. The README itself does not explain how the method works, what data it was trained on, or how to run the code. It only states that this is the official implementation and that more details will be released soon. For a reader, the practical takeaway is that this is a placeholder repository tied to a research paper. The code, weights, dataset preparation, and usage instructions are not present yet. Anyone interested would need to wait for the authors to push the actual implementation, or look up the paper itself for the technical detail that the README leaves out. No license is mentioned in the README.