Human and model observer performance for lesion detection in breast cone beam CT images with the FDK reconstruction

Minah Han, Byeongjoon Kim, Jongduk Baek

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

We investigate the detectability of breast cone beam computed tomography images using human and model observers and the variations of exponent, β, of the inverse power-law spectrum for various reconstruction filters and interpolation methods in the Feldkamp-Davis-Kress (FDK) reconstruction. Using computer simulation, a breast volume with a 50% volume glandular fraction and a 2mm diameter lesion are generated and projection data are acquired. In the FDK reconstruction, projection data are apodized using one of three reconstruction filters; Hanning, Shepp-Logan, or Ram-Lak, and back-projection is performed with and without Fourier interpolation. We conduct signal-known-exactly and background-known-statistically detection tasks. Detectability is evaluated by human observers and their performance is compared with anthropomorphic model observers (a non-prewhitening observer with eye filter (NPWE) and a channelized Hotelling observer with either Gabor channels or dense difference-of-Gaussian channels). Our results show that the NPWE observer with a peak frequency of 7cyc/degree attains the best correlation with human observers for the various reconstruction filters and interpolation methods. We also discover that breast images with smaller β do not yield higher detectability in the presence of quantum noise.

Original languageEnglish
Article numbere0194408
JournalPloS one
Volume13
Issue number3
DOIs
Publication statusPublished - 2018 Mar

Bibliographical note

Funding Information:
This work was supported by Ministry of Science, ICT and Future Planning (IITP-2017-2017-0-01015); National Research Foundation of Korea (2017M2A2A4A01070302, 2015R1C1A1A01052268, 2017M2A2A6A01019663). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Publisher Copyright:
© 2018 Han et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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