Clinical validation pipeline of a deep learning model for segmenting and quantifying intracranial and ventricular volumes on computed tomography.
- DOI
- 10.1038/s41598-026-49678-7
- Published
- 2026 Aug 25
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-49678-7,
title = {Clinical validation pipeline of a deep learning model for segmenting and quantifying intracranial and ventricular volumes on computed tomography.},
author = {Pinto BGG and Olegário TMM and Silva PVA and Ferracioli GM and Paulo AJM and Schumacher K and Cunha MT and Lee HMH and Rodrigues MAS and Kitamura FC and de Paiva JPQ and Loureiro RM},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-49678-7},
url = {https://doi.org/10.1038/s41598-026-49678-7}
}RIS
TY - JOUR TI - Clinical validation pipeline of a deep learning model for segmenting and quantifying intracranial and ventricular volumes on computed tomography. AU - Pinto BGG AU - Olegário TMM AU - Silva PVA AU - Ferracioli GM AU - Paulo AJM AU - Schumacher K AU - Cunha MT AU - Lee HMH AU - Rodrigues MAS AU - Kitamura FC AU - de Paiva JPQ AU - Loureiro RM PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-49678-7 UR - https://doi.org/10.1038/s41598-026-49678-7 ER -
APA
BGG, P., TMM, O., PVA, S., GM, F., AJM, P., K, S., MT, C., HMH, L., MAS, R., FC, K., JPQ, D. P., & RM, L. (2026). Clinical validation pipeline of a deep learning model for segmenting and quantifying intracranial and ventricular volumes on computed tomography.. Scientific reports. https://doi.org/10.1038/s41598-026-49678-7
Source records
- pubmed · retrieved 2026-09-25T15:22:55.644Z