Fellowships, Gifts, and Supported Research
Prior-Knowledge-Independent Deep Learning-Based Reconstruction for Low-Dose Sparse-View Digital Breast Tomosynthesis ·
January 20, 2025
- January 14, 2026
Awarded by: Duke University Provost Fund
· $49,800.00
This first aim of the proposed project is to develop a deep learning technique to compensate for the missing information in sparse-view DBT to eliminate streak artifacts and restore depth resolution. The second aim of this proposed project is to achieve low-dose sparse-view DBT for screening though deep learning-based methodology, integrating functions of denoising and information preservation. Aim-3 of this study is to evaluate the image quality of deep learning-based low-dose sparse-view DBT through reader studies.
Chancellor's Scholarship ·
2018
- 2020
Awarded by: Duke University