Comparison of power spectra for tomosynthesis projections and reconstructed images

Med Phys. 2009 May;36(5):1753-8. doi: 10.1118/1.3116774.

Abstract

Burgess et al. [Med. Phys. 28, 419-437 (2001)] showed that the power spectrum of mammographic breast background follows a power law and that lesion detectability is affected by the power-law exponent beta which measures the amount of structure in the background. Following the study of Burgess et al., the authors measured and compared the power-law exponent of mammographic backgrounds in tomosynthesis projections and reconstructed slices to investigate the effect of tomosynthesis imaging on background structure. Our data set consisted of 55 patient cases. For each case, regions of interest (ROIs) were extracted from both projection images and reconstructed slices. The periodogram of each ROI was computed by taking the squared modulus of the Fourier transform of the ROI. The power-law exponent was determined for each periodogram and averaged across all ROIs extracted from all projections or reconstructed slices for each patient data set. For the projections, the mean beta averaged across the 55 cases was 3.06 (standard deviation of 0.21), while it was 2.87 (0.24) for the corresponding reconstructions. The difference in beta for a given patient between the projection ROIs and the reconstructed ROIs averaged across the 55 cases was 0.194, which was statistically significant (p < 0.001). The 95% CI for the difference between the mean value of beta for the projections and reconstructions was [0.170, 0.218]. The results are consistent with the observation that the amount of breast structure in the tomosynthesis slice is reduced compared to projection mammography and that this may lead to improved lesion detectability.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Breast Neoplasms / diagnostic imaging*
  • Female
  • Humans
  • Imaging, Three-Dimensional / methods*
  • Mammography / methods*
  • Radiographic Image Enhancement / methods*
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity