Sparse View CT Reconstruction Algorithm Based on Non-Local Generalized Total Variation Regularization
CT image reconstruction algorithm based on generalized total variation (TGV) can overcome the staircase effect of total variation (TV) regularization, thereby protecting the structural features of the reconstructed image transition region. Although the TGV reconstruction method is superior to the TV...
Saved in:
Main Authors: | Min JIANG, Hongwei TAO, Kai CHENG |
---|---|
Format: | Article |
Language: | English |
Published: |
Editorial Office of Computerized Tomography Theory and Application
2025-01-01
|
Series: | CT Lilun yu yingyong yanjiu |
Subjects: | |
Online Access: | https://www.cttacn.org.cn/cn/article/doi/10.15953/j.ctta.2023.170 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Sparse Regularization With Reverse Sorted Sum of Squares via an Unrolled Difference-of-Convex Approach
by: Takayuki Sasaki, et al.
Published: (2025-01-01) -
Bregman divergences for physically informed discrepancy measures for learning and computation in thermomechanics
by: Andrieux, Stéphane
Published: (2023-02-01) -
Noise filtering method in images in sparse-view covers
by: Y.V. Goshin, et al.
Published: (2024-06-01) -
Photon-counting-detector CT outperforms state-of-the-art cone-beam and energy-integrated-detector CT in delineation of dental root canals
by: Stephan Rau, et al.
Published: (2025-01-01) -
Effectiveness of skull X-RAY to determine cochlear implant insertion depth
by: Vinay Fernandes, et al.
Published: (2018-09-01)