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Cone-beam breast CT using an offset detector: effect of detector offset and image reconstruction algorithm
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Rev2_OffsetDetector_BreastCT_C ...
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2.154Mb
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Description:
Final Accepted Manuscript
Affiliation
Department of Medical Imaging, The University of ArizonaDepartment of Biomedical Engineering, The University of Arizona
Issue Date
2022-04-07
Metadata
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IOP PublishingCitation
Tseng, H. W., Karellas, A., & Vedantham, S. (2022). Cone-beam breast CT using an offset detector: Effect of detector offset and image reconstruction algorithm. Physics in Medicine and Biology.Journal
Physics in Medicine and BiologyRights
© 2022 Institute of Physics and Engineering in Medicine.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Objective. A dedicated cone-beam breast computed tomography (BCT) using a high-resolution, low-noise detector operating in offset-detector geometry has been developed. This study investigates the effects of varying detector offsets and image reconstruction algorithms to determine the appropriate combination of detector offset and reconstruction algorithm. Approach. Projection datasets (300 projections in 360°) of 30 breasts containing calcified lesions that were acquired using a prototype cone-beam BCT system comprising a 40 × 30 cm flat-panel detector with 1024 × 768 detector pixels were reconstructed using Feldkamp-Davis-Kress (FDK) algorithm and served as the reference. The projection datasets were retrospectively truncated to emulate cone-beam datasets with sinograms of 768 × 768 and 640 × 768 detector pixels, corresponding to 5 cm and 7.5 cm lateral offsets, respectively. These datasets were reconstructed using the FDK algorithm with appropriate weights and an ASD-POCS-based Fast, total variation-Regularized, Iterative, Statistical reconstruction Technique (FRIST), resulting in a total of 4 offset-detector reconstructions (2 detector offsets × 2 reconstruction methods). Signal difference-to-noise ratio (SDNR), variance, and full-width at half-maximum (FWHM) of calcifications in two orthogonal directions were determined from all reconstructions. All quantitative measurements were performed on images in units of linear attenuation coefficient (1/cm). Results. The FWHM of calcifications did not differ (P > 0.262) among reconstruction algorithms and detector formats, implying comparable spatial resolution. For a chosen detector offset, the FRIST algorithm outperformed FDK in terms of variance and SDNR (P < 0.0001). For a given reconstruction method, the 5 cm offset provided better results. Significance. This study indicates the feasibility of using the compressed sensing-based, FRIST algorithm to reconstruct sinograms from offset-detectors. Among the reconstruction methods and detector offsets studied, FRIST reconstructions corresponding to a 30 cm × 30 cm with 5 cm lateral offset, achieved the best performance. A clinical prototype using such an offset geometry has been developed and installed for clinical trials.Note
12 month embargo; published: 7 April 2022ISSN
0031-9155EISSN
1361-6560Version
Final accepted manuscriptSponsors
National Cancer Instituteae974a485f413a2113503eed53cd6c53
10.1088/1361-6560/ac5fe1