Deep Incremental Angle Refinement Model for Limited-Angle CT Reconstruction - A Case Study on Concrete Specimens
Industrial computed tomography (CT) is widely utilized for non-destructive testing and quality control in various industries. However, a common challenge in industrial CT is the presence of artifacts caused by limited angle tomography, where the object cannot be rotated fully due to geometric cons...
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| Format: | Article |
| Language: | deu |
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NDT.net
2025-02-01
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| Series: | e-Journal of Nondestructive Testing |
| Online Access: | https://www.ndt.net/search/docs.php3?id=30719 |
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| author | Xingyu Liu Guangpu Yang Ammar Alsaffar Faizan Ahmad Steffen Kieß Sven Simon |
| author_facet | Xingyu Liu Guangpu Yang Ammar Alsaffar Faizan Ahmad Steffen Kieß Sven Simon |
| author_sort | Xingyu Liu |
| collection | DOAJ |
| description |
Industrial computed tomography (CT) is widely utilized for non-destructive testing and quality control in various industries. However, a common challenge in industrial CT is the presence of artifacts caused by limited angle tomography, where the object cannot be rotated fully due to geometric constraints or time limitations. To eliminate the artifacts, we propose a novel framework based on diffusion model: Deep Incremental Angle Refinement Model (DI-ARM). Our approach leverages the characteristics of CT projection by using reconstructed data of different limited angles as intermediate steps in the training process, replacing the traditional diffusion model of adding random Gaussian noise. This approach ensures data consistency in training process, mitigating the instability caused by sampling randomness of diffusion models. Furthermore, our method requires fewer steps compared to conventional diffusion models, significantly reducing computational resource consumption.
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| format | Article |
| id | doaj-art-0db8af1747d2453cb4b9f15e4bae6263 |
| institution | Kabale University |
| issn | 1435-4934 |
| language | deu |
| publishDate | 2025-02-01 |
| publisher | NDT.net |
| record_format | Article |
| series | e-Journal of Nondestructive Testing |
| spelling | doaj-art-0db8af1747d2453cb4b9f15e4bae62632025-02-06T10:48:18ZdeuNDT.nete-Journal of Nondestructive Testing1435-49342025-02-0130210.58286/30719Deep Incremental Angle Refinement Model for Limited-Angle CT Reconstruction - A Case Study on Concrete SpecimensXingyu Liuhttps://orcid.org/0009-0008-8093-1767Guangpu YangAmmar AlsaffarFaizan AhmadSteffen Kießhttps://orcid.org/0009-0001-0899-0649Sven Simon Industrial computed tomography (CT) is widely utilized for non-destructive testing and quality control in various industries. However, a common challenge in industrial CT is the presence of artifacts caused by limited angle tomography, where the object cannot be rotated fully due to geometric constraints or time limitations. To eliminate the artifacts, we propose a novel framework based on diffusion model: Deep Incremental Angle Refinement Model (DI-ARM). Our approach leverages the characteristics of CT projection by using reconstructed data of different limited angles as intermediate steps in the training process, replacing the traditional diffusion model of adding random Gaussian noise. This approach ensures data consistency in training process, mitigating the instability caused by sampling randomness of diffusion models. Furthermore, our method requires fewer steps compared to conventional diffusion models, significantly reducing computational resource consumption. https://www.ndt.net/search/docs.php3?id=30719 |
| spellingShingle | Xingyu Liu Guangpu Yang Ammar Alsaffar Faizan Ahmad Steffen Kieß Sven Simon Deep Incremental Angle Refinement Model for Limited-Angle CT Reconstruction - A Case Study on Concrete Specimens e-Journal of Nondestructive Testing |
| title | Deep Incremental Angle Refinement Model for Limited-Angle CT Reconstruction - A Case Study on Concrete Specimens |
| title_full | Deep Incremental Angle Refinement Model for Limited-Angle CT Reconstruction - A Case Study on Concrete Specimens |
| title_fullStr | Deep Incremental Angle Refinement Model for Limited-Angle CT Reconstruction - A Case Study on Concrete Specimens |
| title_full_unstemmed | Deep Incremental Angle Refinement Model for Limited-Angle CT Reconstruction - A Case Study on Concrete Specimens |
| title_short | Deep Incremental Angle Refinement Model for Limited-Angle CT Reconstruction - A Case Study on Concrete Specimens |
| title_sort | deep incremental angle refinement model for limited angle ct reconstruction a case study on concrete specimens |
| url | https://www.ndt.net/search/docs.php3?id=30719 |
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