Human observer performance on in-plane digital breast tomosynthesis images: Effects of reconstruction filters and data acquisition angles on signal detection

Changwoo Lee, Minah Han, Jongduk Baek

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

For digital breast tomosynthesis (DBT) systems, we investigate the effects of the reconstruction filters for different data acquisition angles on signal detection. We simulated a breast phantom with a 30% volume glandular fraction (VGF) of breast anatomy using the power law spectrum and modeled the breast mass as a spherical object with a 1 mm diameter. Projection data were acquired using two different data acquisition angles and numbers of projection view pairs, and in-plane breast images were reconstructed using the Feldkamp-Davis-Kress (FDK) algorithm with three different reconstruction filter schemes. To measure the ability to detect a signal, we conducted the human observer study with a binary detection task and compared the signal detectability of human to that of channelized Hotelling observer (CHO) with Laguerre-Gauss (LG) channels and dense difference-of-Gaussian (D-DOG) channels. We also measured the contrast-to-noise ratio (CNR), signal power spectrum (SPS), and β values of the anatomical noise power spectrum (NPS) to show the association between human observer performance and these traditional metrics. Our results show that using a slice thickness (ST) filter degraded the signal detection performance of human observers at the same data acquisition angle. This could be predicted by D-DOG CHO with internal noise, but the correlation between the traditional metrics and signal detectability was not observed in this work.

Original languageEnglish
Article numbere0229915
JournalPloS one
Volume15
Issue number3
DOIs
Publication statusPublished - 2020

Bibliographical note

Funding Information:
This research was supported by Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Ministry of Science and ICT (2018M3A9H6081482, 2019R1A2C2084936, 2018M3A9H6081483). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

All Science Journal Classification (ASJC) codes

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

Fingerprint Dive into the research topics of 'Human observer performance on in-plane digital breast tomosynthesis images: Effects of reconstruction filters and data acquisition angles on signal detection'. Together they form a unique fingerprint.

Cite this