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A general method for cupping artifact correction of cone-beam breast computed tomography images

  • Xiaolei Qu
  • , Chao Jen Lai
  • , Yuncheng Zhong
  • , Ying Yi
  • , Chris C. Shaw*
  • *Corresponding author for this work
  • The University of Tokyo
  • University of Texas MD Anderson Cancer Center

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: Cone-beam breast computed tomography (CBBCT), a promising breast cancer diagnostic technique, has been under investigation for the past decade. However, owing to scattered radiation and beam hardening, CT numbers are not uniform on CBBCT images. This is known as cupping artifact, and it presents an obstacle for threshold-based volume segmentation. In this study, we proposed a general post-reconstruction method for cupping artifact correction. Methods: There were four steps in the proposed method. First, three types of local region histogram peaks were calculated: adipose peaks with low CT numbers, glandular peaks with high CT numbers, and unidentified peaks. Second, a linear discriminant analysis classifier, which was trained by identified adipose and glandular peaks, was employed to identify the unidentified peaks as adipose or glandular peaks. Third, adipose background signal profile was fitted according to the adipose peaks using the least squares method. Finally, the adipose background signal profile was subtracted from original image to obtain cupping corrected image Results: In experimental study, standard deviation of adipose tissue CT numbers was obviously reduced and the CT numbers were more uniform after cupping correction by proposed method; in simulation study, root-mean-square errors were significantly reduced for both symmetric and asymmetric cupping artifacts, indicating that the proposed method was effective to both artifacts. Conclusions: A general method without a circularly symmetric assumption was proposed to correct cupping artifacts in CBBCT images for breast. It may be properly applied to images of real patient breasts with natural pendent geometry.

Original languageEnglish
Pages (from-to)1233-1246
Number of pages14
JournalInternational Journal of Computer Assisted Radiology and Surgery
Volume11
Issue number7
DOIs
StatePublished - 1 Jul 2016
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Background fitting
  • CT number uniformity
  • Cone-beam breast CT
  • Cupping artifact correction

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