Characterization of masses in digital breast tomosynthesis: Comparison of machine learning in projection views and reconstructed slices
Abstract
In digital breast tomosynthesis (DBT), quasi‐three‐dimensional (3D) structural information is reconstructed from a small number of 2D projection view (PV) mammograms acquired over a limited angular range. The authors developed preliminary computer‐aided diagnosis (CADx) methods for classification of malignant and benign masses and compared the effectiveness of analyzing lesion characteristics in the reconstructed DBT slices and in the PVs.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jun 15, 2010
- Source ID
- 10.1118/1.3432570
Entities
People
- Berkman Sahiner
- Daniel B. Kopans
- Heang‐ping Chan
- Jun Wei
- Lubomir Hadjiiski
- Mark A. Helvie
- Richard H. Moore
- Ted Way
- Yiheng Zhang
- Yi‐ta Wu
Organizations
- United States Army Medical Research and Development Command
- United States Public Health Service