Deep-learning-based attenuation map generation in kidney single photon emission computed tomography
The study successfully developed and optimized a deep learning algorithm for generating synthetic μ-maps in kidney SPECT images, demonstrating the potential to transition from conventional SPECT/CT to CT-free SPECT imaging for GFR measurement. This advancement represents a significant step towards enhancing patient safety and efficiency in nuclear medicine.
Authors
- Dongkyu Oh (ORCID: https://orcid.org/0000-0002-7935-3479)
- Kyounghyoun Kwon (ORCID: https://orcid.org/0000-0002-4969-9655)
- Ji Hye Kim (ORCID: https://orcid.org/0000-0002-3912-7709)
- Jihyung Yoo
- Won Woo Lee (ORCID: https://orcid.org/0000-0002-9188-6921)
Institutions
- Seoul National University of Science and Technology (KR)
- Seoul National University (KR)
- New Generation University College (ET)
- Seoul National University Hospital (KR)
- Seoul National University Bundang Hospital (KR)
- National University College (PR)
Publication Details
- Journal
- EJNMMI Physics
- Published
- 2024-10-12
- DOI
- https://doi.org/10.1186/s40658-024-00686-4
- Citations
- 4
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea