Estimation of fatty acid composition in mammary adipose tissue using deep neural network with unsupervised training
The results in this study suggest that the proposed FAC-Net can be used to measure the FAC of mammary adipose tissue from gradient-echo MRI data of the breast.
Authors
- Dominik M. Nickel (ORCID: https://orcid.org/0000-0002-0360-7233)
- Eileen Chang
- Linda Moy (ORCID: https://orcid.org/0000-0001-9564-9360)
- Sungheon Kim (ORCID: https://orcid.org/0000-0002-6288-0678)
- Eralda Mema (ORCID: https://orcid.org/0000-0002-0238-0516)
- Michele Drotman (ORCID: https://orcid.org/0000-0003-4632-6949)
- Elizabeth G. Lane (ORCID: https://orcid.org/0000-0002-1462-3706)
- Katerina Dodelzon (ORCID: https://orcid.org/0000-0001-9138-4385)
- Anika L. McGrath (ORCID: https://orcid.org/0000-0001-5843-7457)
- Allison Levy
- M. Reichmann
- Suneeta Chaudhary
- Katherine Simon (ORCID: https://orcid.org/0000-0001-9232-2653)
Institutions
- Cornell University (US)
- Siemens Healthineers (Germany) (DE)
- New York University (US)
Publication Details
- Journal
- Magnetic Resonance in Medicine
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1002/mrm.30401
- Citations
- 1
- Primary Topic
- Cardiovascular Disease and Adiposity
- Type
- article
- Field-Weighted Citation Impact
- 0.40
Funders
- National Cancer Institute