Evaluating Gates’ GFR accuracy in renal tumor patients through integration of standalone CT-derived renal depth estimation via deep learning segmentation: a preliminary study
- DOI
- 10.1186/s12882-026-05226-z
- Published
- 2026-07-27
- Container
- BMC Nephrology
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s12882-026-05226-z,
title = {Evaluating Gates’ GFR accuracy in renal tumor patients through integration of standalone CT-derived renal depth estimation via deep learning segmentation: a preliminary study},
author = {Chunxing Wu and Guangfeng Chen and Qing Liao and Feng Zhang and Liangjun Xie and Yueming Zha},
year = {2026},
journal = {BMC Nephrology},
doi = {10.1186/s12882-026-05226-z},
url = {https://doi.org/10.1186/s12882-026-05226-z}
}RIS
TY - JOUR TI - Evaluating Gates’ GFR accuracy in renal tumor patients through integration of standalone CT-derived renal depth estimation via deep learning segmentation: a preliminary study AU - Chunxing Wu AU - Guangfeng Chen AU - Qing Liao AU - Feng Zhang AU - Liangjun Xie AU - Yueming Zha PY - 2026 JO - BMC Nephrology DO - 10.1186/s12882-026-05226-z UR - https://doi.org/10.1186/s12882-026-05226-z ER -
APA
Wu, C., Chen, G., Liao, Q., Zhang, F., Xie, L., & Zha, Y. (2026). Evaluating Gates’ GFR accuracy in renal tumor patients through integration of standalone CT-derived renal depth estimation via deep learning segmentation: a preliminary study. BMC Nephrology. https://doi.org/10.1186/s12882-026-05226-z
Source records
- crossref · retrieved 2026-11-09T21:59:59.213Z