Imaging phenotype evaluation from digital breast tomosynthesis data: A preliminary study
Combining the proposed phenotype classifier with the commonly used malignant-benign-normal classification enables a more detailed assessment of digital breast tomosynthesis images.
Authors
- Satu I. Inkinen (ORCID: https://orcid.org/0000-0002-9774-8925)
- Helinä Heino (ORCID: https://orcid.org/0000-0002-1345-9094)
- Pieta S. Ipatti (ORCID: https://orcid.org/0000-0001-8637-4238)
- Jarmo Reponen (ORCID: https://orcid.org/0000-0003-2306-3111)
- Miika T. Nieminen (ORCID: https://orcid.org/0000-0002-2300-2848)
- Antti Isosalo (ORCID: https://orcid.org/0000-0002-5335-7535)
- Lucia Prostredná
Institutions
- University of Helsinki (FI)
- Oulu University Hospital (FI)
- Oulu University of Applied Sciences (FI)
- University of Oulu (FI)
Publication Details
- Journal
- Computers in Biology and Medicine
- Published
- 2024-10-24
- DOI
- https://doi.org/10.1016/j.compbiomed.2024.109285
- Primary Topic
- Digital Radiography and Breast Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Academy of Finland
- Suomen Kulttuurirahasto
- Jane ja Aatos Erkon Säätiö
- Teknologiateollisuuden 100-Vuotisjuhlasäätiö
- Jenny ja Antti Wihurin Rahasto