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An attenuation field network for dedicated cone beam breast CT with short scan and offset detector geometry.
- Source :
-
Scientific Reports . 1/3/2024, Vol. 13 Issue 1, p1-13. 13p. - Publication Year :
- 2024
-
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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 13
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Scientific Reports
- Publication Type :
- Academic Journal
- Accession number :
- 174579677
- Full Text :
- https://doi.org/10.1038/s41598-023-51077-1