Sparse-view Material Decomposition for Spectral X-ray CT using Neural Radiance Fields
Photon-counting X-ray detectors, in contrast to conventional flat panel detectors, have the capability of distinguishing between photons with different energies, and have been leveraged for material decomposition tasks for materials with similar X-ray attenuation properties. However, as the energy...
Saved in:
Main Authors: | Takumi Hotta, Tatsuya Yatagawa, Yutaka Ohtake, Toru Aoki |
---|---|
Format: | Article |
Language: | deu |
Published: |
NDT.net
2025-02-01
|
Series: | e-Journal of Nondestructive Testing |
Online Access: | https://www.ndt.net/search/docs.php3?id=30727 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Narrow-Energy-Width CT Based on Multivoltage X-Ray Image Decomposition
by: Jiaotong Wei, et al.
Published: (2017-01-01) -
Rugularizing generalizable neural radiance field with limited-view images
by: Wei Sun, et al.
Published: (2024-12-01) -
Learning-Based Image Restorations of Sparse-View CT Data: Is It Reliable?
by: Philip Maurice Trapp, et al.
Published: (2025-02-01) -
Sparse View CT Reconstruction Algorithm Based on Non-Local Generalized Total Variation Regularization
by: Min JIANG, et al.
Published: (2025-01-01) -
‘Florida Radiance’ Strawberry
by: Vance M. Whitaker, et al.
Published: (2013-07-01)