PMID- 36710712
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20230321
LR  - 20231206
IS  - 1095-9114 (Electronic)
IS  - 0895-3996 (Linking)
VI  - 31
IP  - 2
DP  - 2023
TI  - Correction of motion artifact in CL based on MAFusNet.
PG  - 393-407
LID - 10.3233/XST-221335 [doi]
AB  - Computed laminography (CL) is one of the best methods for nondestructive testing 
      of plate-like objects. If the object and the detector move continually while the 
      scanning is being done, the data acquisition efficiency of CL will be 
      significantly increased. However, the projection images will contain motion 
      artifact as a result. A multi-angle fusion network (MAFusNet) is presented in 
      order to correct the motion artifact of CL projection images considering the 
      properties of CL projection images. The multi-angle fusion module significantly 
      increases the ability of MAFusNet to deblur by using data from nearby projection 
      images, and the feature fusion module lessens information loss brought on by data 
      flow between the encoders. In contrast to conventional deblurring networks, the 
      MAFusNet network employs synthetic datasets for training and performed well on 
      realistic data, proving the network's outstanding generalization. The multi-angle 
      fusion-based network has a significant improvement in the correction effect of CL 
      motion artifact through ablation study and comparison with existing classical 
      deblurring networks, and the synthetic training dataset can also significantly 
      lower the training cost, which can effectively improve the quality and efficiency 
      of CL imaging in industrial nondestructive testing.
FAU - Jia, Tong
AU  - Jia T
AD  - Beijing Engineering Research Center of Radiographic Techniques and Equipment, 
      Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China.
AD  - School of Nuclear Science and Technology, University of Chinese Academy of 
      Sciences, Beijing, China.
FAU - Shi, Liu
AU  - Shi L
AD  - Beijing Engineering Research Center of Radiographic Techniques and Equipment, 
      Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China.
AD  - School of Nuclear Science and Technology, University of Chinese Academy of 
      Sciences, Beijing, China.
FAU - Wei, Cunfeng
AU  - Wei C
AD  - Beijing Engineering Research Center of Radiographic Techniques and Equipment, 
      Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China.
AD  - School of Nuclear Science and Technology, University of Chinese Academy of 
      Sciences, Beijing, China.
FAU - Shi, Rongjian
AU  - Shi R
AD  - Beijing Engineering Research Center of Radiographic Techniques and Equipment, 
      Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China.
FAU - Liu, Baodong
AU  - Liu B
AD  - Beijing Engineering Research Center of Radiographic Techniques and Equipment, 
      Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China.
AD  - School of Nuclear Science and Technology, University of Chinese Academy of 
      Sciences, Beijing, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - Netherlands
TA  - J Xray Sci Technol
JT  - Journal of X-ray science and technology
JID - 9000080
SB  - IM
OTO - NOTNLM
OT  - Computed laminography
OT  - deep learning
OT  - image deblurring
OT  - rotational motion blur
EDAT- 2023/01/31 06:00
MHDA- 2023/01/31 06:01
CRDT- 2023/01/30 03:43
PHST- 2023/01/31 06:00 [pubmed]
PHST- 2023/01/31 06:01 [medline]
PHST- 2023/01/30 03:43 [entrez]
AID - XST221335 [pii]
AID - 10.3233/XST-221335 [doi]
PST - ppublish
SO  - J Xray Sci Technol. 2023;31(2):393-407. doi: 10.3233/XST-221335.