A deep learning framework for efficient analysis of breast volume and fibroglandular tissue using MR data with strong artifacts
2019 | journal article. A publication with affiliation to the University of Göttingen.
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A deep learning framework for efficient analysis of breast volume and fibroglandular tissue using MR data with strong artifacts
Ivanovska, T. ; Jentschke, T. G.; Daboul, A.; Hegenscheid, K.; Volzke, H. & Wörgötter, F. (2019)
International Journal of Computer Assisted Radiology and Surgery,. DOI: https://doi.org/10.1007/s11548-019-01928-y
Documents & Media
Details
- Authors
- Ivanovska, Tatyana ; Jentschke, Thomas G.; Daboul, Amro; Hegenscheid, Katrin; Volzke, Henry; Wörgötter, Florentin
- Abstract
- The main purpose of this work is to develop, apply, and evaluate an efficient approach for breast density estimation in magnetic resonance imaging data, which contain strong artifacts including intensity inhomogeneities.
- Issue Date
- 2019
- Journal
- International Journal of Computer Assisted Radiology and Surgery
- ISSN
- 1861-6410; 1861-6429
- eISSN
- 1861-6429
- Language
- English
