Unsupervised Denoising of Real Clinical Low Dose Liver CT with Perceptual Attention Networks

Jingxi Pu, Tonghua Liu, Zhilin Guan, Siqiao Li, Yang Ming et al.|May 1, 2026arXiv

Key Takeaway

You can denoise real clinical CT images without paired training data by using unsupervised learning with perceptual loss, making it practical for hospitals that can't easily create labeled datasets.

Summary

This paper tackles noise in low-dose CT scans—a real clinical problem where reducing radiation exposure creates grainy images that are hard for doctors to read.

efficiency evaluation applications

Key Terms

perceptual-loss u-net attention-mechanism residual-network unsupervised-learning