Optimization-based image reconstruction from low-dose patient breast CT Data

Junguo Bian, Kai Yang, Emil Y. Sidky, John M Boone, Xiaochuan Pan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Current dedicated breast-CT prototypes use analytic-based algorithms such as FDK for image reconstruction, which require a large number of densely sampled views. Because the total imaging dose delivered to a patient in a breast-CT scan is kept about the same as that in a typical two-view mammography exam, the use of a large number of views thus can lead to projection data of low SNR and images with high noise, which makes reconstruction improvement challenging. Recently, there exists increased interest in development and evaluation of optimization-based (i.e. iterative) image reconstruction algorithms for low-dose cone-beam CT (CBCT). In the work, we focus on investigation of optimization-based image reconstruction for low-dose breast CT by tailoring a TV-minimization-based algorithm, adaptive-steep-descent (ASD)-projection-onto- convex-set (POCS) algorithm, for image reconstruction from low-SNR patient data. We performed inverse-crime studies for verifying if the algorithm is solving the designed optimization program, and studied the effect of optimization program parameter, ε, on the reconstruction images. We also studied the change of image power spectra with ε and iteration numbers. The results indicate that optimization-based algorithms may improve image quality over analytic-based algorithm for low-dose dedicated breast CT.

Original languageEnglish (US)
Title of host publicationIEEE Nuclear Science Symposium Conference Record
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479905348
DOIs
StatePublished - 2013
Event2013 60th IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2013 - Seoul, Korea, Republic of
Duration: Oct 27 2013Nov 2 2013

Other

Other2013 60th IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2013
CountryKorea, Republic of
CitySeoul
Period10/27/1311/2/13

Fingerprint

Computer-Assisted Image Processing
image reconstruction
breast
Breast
dosage
optimization
projection
crime
descent
Crime
Mammography
iteration
Noise
power spectra
cones
prototypes
evaluation

ASJC Scopus subject areas

  • Radiation
  • Nuclear and High Energy Physics
  • Radiology Nuclear Medicine and imaging

Cite this

Bian, J., Yang, K., Sidky, E. Y., Boone, J. M., & Pan, X. (2013). Optimization-based image reconstruction from low-dose patient breast CT Data. In IEEE Nuclear Science Symposium Conference Record [6829371] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NSSMIC.2013.6829371

Optimization-based image reconstruction from low-dose patient breast CT Data. / Bian, Junguo; Yang, Kai; Sidky, Emil Y.; Boone, John M; Pan, Xiaochuan.

IEEE Nuclear Science Symposium Conference Record. Institute of Electrical and Electronics Engineers Inc., 2013. 6829371.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Bian, J, Yang, K, Sidky, EY, Boone, JM & Pan, X 2013, Optimization-based image reconstruction from low-dose patient breast CT Data. in IEEE Nuclear Science Symposium Conference Record., 6829371, Institute of Electrical and Electronics Engineers Inc., 2013 60th IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2013, Seoul, Korea, Republic of, 10/27/13. https://doi.org/10.1109/NSSMIC.2013.6829371
Bian J, Yang K, Sidky EY, Boone JM, Pan X. Optimization-based image reconstruction from low-dose patient breast CT Data. In IEEE Nuclear Science Symposium Conference Record. Institute of Electrical and Electronics Engineers Inc. 2013. 6829371 https://doi.org/10.1109/NSSMIC.2013.6829371
Bian, Junguo ; Yang, Kai ; Sidky, Emil Y. ; Boone, John M ; Pan, Xiaochuan. / Optimization-based image reconstruction from low-dose patient breast CT Data. IEEE Nuclear Science Symposium Conference Record. Institute of Electrical and Electronics Engineers Inc., 2013.
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