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PreprintAll rights reservedmedRxiv

Urinary stone segmentation: A computationally efficient yet consistently effective approach using image processing

  • B. D. Le
  • S.-H. Yang
  • H. T. Nguyen
  • K.-J. Oh
  • I. Park1
  1. 1Department of Radiology, Chonnam National University Medical School and Hospital, Korea
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Cite

BibTeXRIS
BibTeX
@misc{le2026urinary,
  title = {{Urinary stone segmentation: A computationally efficient yet consistently effective approach using image processing}},
  author = {B. D. Le and S.-H. Yang and H. T. Nguyen and K.-J. Oh and I. Park},
  howpublished = {medRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.16.26357464},
  url = {https://www.medrxiv.org/content/10.64898/2026.09.16.26357464v1},
}
RIS
TY  - UNPB
TI  - Urinary stone segmentation: A computationally efficient yet consistently effective approach using image processing
AU  - B. D. Le
AU  - S.-H. Yang
AU  - H. T. Nguyen
AU  - K.-J. Oh
AU  - I. Park
PY  - 2026
DA  - 2026/09/16
PB  - medRxiv
DO  - 10.64898/2026.09.16.26357464
UR  - https://www.medrxiv.org/content/10.64898/2026.09.16.26357464v1
ER  -