Super-Energy-Resolution Material Decomposition for Spectral Photon-Counting CT Using Pixel-Wise Learning - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Access Année : 2021

Super-Energy-Resolution Material Decomposition for Spectral Photon-Counting CT Using Pixel-Wise Learning

Résumé

Spectral photon-counting CT offers novel potentialities to achieve quantitative decomposition of material components, in comparison with traditional energy-integrating CT or dual-energy CT. Nonetheless, achieving accurate material decomposition, especially for low-concentration materials, is still extremely challenging for current sCT, due to restricted energy resolution stemming from the trade-off between the number of energy bins and undesired factors such as quantum noise. We propose to improve material decomposition by introducing the notion of super-energy-resolution in sCT. The super-energyresolution material decomposition consists in learning the relationship between simulation and physical phantoms in image domain. To this end, a coupled dictionary learning method is utilized to learn such relationship in a pixel-wise way. The results on both physical phantoms and in vivo data showed that for the same decomposition method using lasso regularization, the proposed super-energy-resolution method achieves much higher decomposition accuracy and detection ability in contrast to traditional image-domain decomposition method using L1-norm regularization. INDEX TERMS X-ray CT, material decomposition, photon-counting detector, super energy resolution.
Fichier principal
Vignette du fichier
Xie Bingqing_IeeeAccess_2021.pdf (2.1 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04455271 , version 1 (13-02-2024)

Identifiants

Citer

Bingqing Xie, Yuemin Zhu, Pei Niu, Ting Su, Feng Yang, et al.. Super-Energy-Resolution Material Decomposition for Spectral Photon-Counting CT Using Pixel-Wise Learning. IEEE Access, 2021, 9 (3), pp.168485 - 168495. ⟨10.1109/access.2021.3134636⟩. ⟨hal-04455271⟩
23 Consultations
14 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More