Ring Artifacts Removal Based on Implicit Neural Representation of Sinogram Data

Autor:	Shi, Ligen, Jiang, Xu, Liu, YunZe, Liu, Chang, Yang, Ping, Guo, Shifeng, Zhao, Xing
Rok vydání:	2024
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing 68U05 65D18 I.4.5 I.4.10
Druh dokumentu:	Working Paper
Popis:	Inconsistent responses of X-ray detector elements lead to stripe artifacts in the sinogram data, which manifest as ring artifacts in the reconstructed CT images, severely degrading image quality. This paper proposes a method for correcting stripe artifacts in the sinogram data. The proposed method leverages implicit neural representation (INR) to correct defective pixel response values using implicit continuous functions and simultaneously learns stripe features in the angular direction of the sinogram data. These two components are combined within an optimization constraint framework, achieving unsupervised iterative correction of stripe artifacts in the projection domain. Experimental results demonstrate that the proposed method significantly outperforms current state-of-the-art techniques in removing ring artifacts while maintaining the clarity of CT images. Comment: 10 pages, 11 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2409.15731 Zobrazit plný text záznamu View this record from Arxiv