Convolutional neural network model observers discount signal-like anatomical structures during search in virtual digital breast tomosynthesis phantoms
We show that CNNs are a more suitable model observer for search tasks. Like radiologists but not traditional LMOs, CNNs can discount false positives arising from anatomical backgrounds.
Authors
- Susan P. Weinstein (ORCID: https://orcid.org/0000-0001-6159-1500)
- Craig K. Abbey (ORCID: https://orcid.org/0000-0003-4608-9402)
- Andrew D. A. Maidment (ORCID: https://orcid.org/0000-0003-1074-7063)
- Aditya Jonnalagadda
- Bruno Barufaldi (ORCID: https://orcid.org/0000-0003-3954-3611)
- Miguel P. Eckstein (ORCID: https://orcid.org/0000-0002-5528-355X)
Institutions
- University of California, Santa Barbara (US)
- University of Pennsylvania (US)
Publication Details
- Journal
- Journal of Medical Imaging
- Published
- 2025-10-16
- DOI
- https://doi.org/10.1117/1.jmi.12.5.051809
- Primary Topic
- Digital Radiography and Breast Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00