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- Publisher Website: 10.1007/978-3-030-22368-7_12
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Conference Paper: An Iteration Method for X-Ray CT Reconstruction from Variable-Truncation Projection Data
| Title | An Iteration Method for X-Ray CT Reconstruction from Variable-Truncation Projection Data |
|---|---|
| Authors | |
| Keywords | In-situ X-ray CT Noise estimation Occluded projection data Sparse representation |
| Issue Date | 2019 |
| Citation | Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2019, v. 11603 LNCS, p. 144-155 How to Cite? |
| Abstract | In this paper, we investigate the in-situ X-ray CT reconstruction from occluded projection data. For each X-ray beam, we propose a method to determine whether it passes through a measured object by comparing the observed data before and after the measured object is placed. Therefore, we can obtain a prior knowledge of the object, that is some points belonging to the background, from the X-ray beam paths that do not pass through the object. We incorporate this prior knowledge into the sparse representation method for in-situ X-ray CT reconstruction from occluded projection data. In addition, the regularization parameter can be determined easily using the artifact severity estimation on the identified background points. Numerical experiments on simulated data with different noise levels are conducted to verify the effectiveness of the proposed method. |
| Persistent Identifier | http://hdl.handle.net/10722/363328 |
| ISSN | 2023 SCImago Journal Rankings: 0.606 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Huo, Limei | - |
| dc.contributor.author | Luo, Shousheng | - |
| dc.contributor.author | Dong, Yiqiu | - |
| dc.contributor.author | Tai, Xue Cheng | - |
| dc.contributor.author | Wang, Yang | - |
| dc.date.accessioned | 2025-10-10T07:46:04Z | - |
| dc.date.available | 2025-10-10T07:46:04Z | - |
| dc.date.issued | 2019 | - |
| dc.identifier.citation | Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2019, v. 11603 LNCS, p. 144-155 | - |
| dc.identifier.issn | 0302-9743 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/363328 | - |
| dc.description.abstract | In this paper, we investigate the in-situ X-ray CT reconstruction from occluded projection data. For each X-ray beam, we propose a method to determine whether it passes through a measured object by comparing the observed data before and after the measured object is placed. Therefore, we can obtain a prior knowledge of the object, that is some points belonging to the background, from the X-ray beam paths that do not pass through the object. We incorporate this prior knowledge into the sparse representation method for in-situ X-ray CT reconstruction from occluded projection data. In addition, the regularization parameter can be determined easily using the artifact severity estimation on the identified background points. Numerical experiments on simulated data with different noise levels are conducted to verify the effectiveness of the proposed method. | - |
| dc.language | eng | - |
| dc.relation.ispartof | Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics | - |
| dc.subject | In-situ X-ray CT | - |
| dc.subject | Noise estimation | - |
| dc.subject | Occluded projection data | - |
| dc.subject | Sparse representation | - |
| dc.title | An Iteration Method for X-Ray CT Reconstruction from Variable-Truncation Projection Data | - |
| dc.type | Conference_Paper | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1007/978-3-030-22368-7_12 | - |
| dc.identifier.scopus | eid_2-s2.0-85068447157 | - |
| dc.identifier.volume | 11603 LNCS | - |
| dc.identifier.spage | 144 | - |
| dc.identifier.epage | 155 | - |
| dc.identifier.eissn | 1611-3349 | - |
