Combined application of deep learning and conventional computer vision for kidney ultrasound image classification in chronic kidney disease: preliminary study
The integration of DL with automated feature extraction enables accurate classification of CKD using minimal user input. This proof-of-concept study highlights the potential of combining artificial intelligence-driven analysis with traditional metrics to serve as a noninvasive adjunct for CKD diagnosis and monitoring.
Authors
- Connie Ge
- Junbong Jang (ORCID: https://orcid.org/0000-0001-9317-6520)
- Young H. Kim (ORCID: https://orcid.org/0000-0002-0206-5663)
- Hajeong Lee (ORCID: https://orcid.org/0000-0002-1873-1587)
- Patrick Tomas Svrcek
Institutions
- Korea Advanced Institute of Science and Technology (KR)
- University of Massachusetts Chan Medical School (US)
- Seoul National University Hospital (KR)
Publication Details
- Journal
- ULTRASONOGRAPHY
- Published
- 2025-08-04
- DOI
- https://doi.org/10.14366/usg.25074
- Citations
- 1
- Primary Topic
- Renal and Vascular Pathologies
- Type
- article
- Field-Weighted Citation Impact
- 1.52