An attenuation field network for dedicated cone beam breast CT with short scan and offset detector geometry
Abstract The feasibility of full-scan, offset-detector geometry cone-beam CT has been demonstrated for several clinical applications. For full-scan acquisition with offset-detector geometry, data redundancy from complementary views can be exploited during image reconstruction. Envisioning an upright...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-51077-1 |
| _version_ | 1797363443848708096 |
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| author | Zhiyang Fu Hsin Wu Tseng Srinivasan Vedantham |
| author_facet | Zhiyang Fu Hsin Wu Tseng Srinivasan Vedantham |
| author_sort | Zhiyang Fu |
| collection | DOAJ |
| description | Abstract The feasibility of full-scan, offset-detector geometry cone-beam CT has been demonstrated for several clinical applications. For full-scan acquisition with offset-detector geometry, data redundancy from complementary views can be exploited during image reconstruction. Envisioning an upright breast CT system, we propose to acquire short-scan data in conjunction with offset-detector geometry. To tackle the resulting incomplete data, we have developed a self-supervised attenuation field network (AFN). AFN leverages the inherent redundancy of cone-beam CT data through coordinate-based representation and known imaging physics. A trained AFN can query attenuation coefficients using their respective coordinates or synthesize projection data including the missing projections. The AFN was evaluated using clinical cone-beam breast CT datasets (n = 50). While conventional analytical and iterative reconstruction methods failed to reconstruct the incomplete data, AFN reconstruction was not statistically different from the reference reconstruction obtained using full-scan, full-detector data in terms of image noise, image contrast, and the full width at half maximum of calcifications. This study indicates the feasibility of a simultaneous short-scan and offset-detector geometry for dedicated breast CT imaging. The proposed AFN technique can potentially be expanded to other cone-beam CT applications. |
| first_indexed | 2024-03-08T16:21:27Z |
| format | Article |
| id | doaj.art-64afc4f3e58a4141836ff39ff97adfaf |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-08T16:21:27Z |
| publishDate | 2024-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-64afc4f3e58a4141836ff39ff97adfaf2024-01-07T12:21:29ZengNature PortfolioScientific Reports2045-23222024-01-0114111310.1038/s41598-023-51077-1An attenuation field network for dedicated cone beam breast CT with short scan and offset detector geometryZhiyang Fu0Hsin Wu Tseng1Srinivasan Vedantham2Department of Medical Imaging, The University of ArizonaDepartment of Medical Imaging, The University of ArizonaDepartment of Medical Imaging, The University of ArizonaAbstract The feasibility of full-scan, offset-detector geometry cone-beam CT has been demonstrated for several clinical applications. For full-scan acquisition with offset-detector geometry, data redundancy from complementary views can be exploited during image reconstruction. Envisioning an upright breast CT system, we propose to acquire short-scan data in conjunction with offset-detector geometry. To tackle the resulting incomplete data, we have developed a self-supervised attenuation field network (AFN). AFN leverages the inherent redundancy of cone-beam CT data through coordinate-based representation and known imaging physics. A trained AFN can query attenuation coefficients using their respective coordinates or synthesize projection data including the missing projections. The AFN was evaluated using clinical cone-beam breast CT datasets (n = 50). While conventional analytical and iterative reconstruction methods failed to reconstruct the incomplete data, AFN reconstruction was not statistically different from the reference reconstruction obtained using full-scan, full-detector data in terms of image noise, image contrast, and the full width at half maximum of calcifications. This study indicates the feasibility of a simultaneous short-scan and offset-detector geometry for dedicated breast CT imaging. The proposed AFN technique can potentially be expanded to other cone-beam CT applications.https://doi.org/10.1038/s41598-023-51077-1 |
| spellingShingle | Zhiyang Fu Hsin Wu Tseng Srinivasan Vedantham An attenuation field network for dedicated cone beam breast CT with short scan and offset detector geometry Scientific Reports |
| title | An attenuation field network for dedicated cone beam breast CT with short scan and offset detector geometry |
| title_full | An attenuation field network for dedicated cone beam breast CT with short scan and offset detector geometry |
| title_fullStr | An attenuation field network for dedicated cone beam breast CT with short scan and offset detector geometry |
| title_full_unstemmed | An attenuation field network for dedicated cone beam breast CT with short scan and offset detector geometry |
| title_short | An attenuation field network for dedicated cone beam breast CT with short scan and offset detector geometry |
| title_sort | attenuation field network for dedicated cone beam breast ct with short scan and offset detector geometry |
| url | https://doi.org/10.1038/s41598-023-51077-1 |
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