Frequency-based texture analysis of non-Gaussian properties of digital breast tomosynthesis images and comparison across two vendors
Significant differences in perception of breast parenchyma textures among two DBT vendors were demonstrated via higher-order non-Gaussian statistical properties. This finding extends previously observed differences in anatomical noise power spectra in DBT images and provides quantitative evidence to support caution in across-vendor comparative reading and will be beneficial to facilitate future development of vendor-neutral artificial intelligence algorithms for breast cancer screening.
Authors
- Craig K. Abbey (ORCID: https://orcid.org/0000-0003-4608-9402)
- Bob Liu (ORCID: https://orcid.org/0000-0001-6221-1047)
- Kai Yang (ORCID: https://orcid.org/0000-0002-7428-8401)
- Bruno Barufaldi (ORCID: https://orcid.org/0000-0003-3954-3611)
- Theodore A. Marschall (ORCID: https://orcid.org/0000-0002-3200-8846)
- Xinhua Li (ORCID: https://orcid.org/0000-0001-5072-3686)
Institutions
- University of California, Santa Barbara (US)
- Massachusetts General Hospital (US)
- University of Pennsylvania (US)
Publication Details
- Journal
- Journal of Medical Imaging
- Published
- 2025-03-20
- DOI
- https://doi.org/10.1117/1.jmi.12.s2.s22004
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00