Pre-Deployment Evaluation of a Remote Service for Short-Axis Cardiac MRI Segmentation.
SH, C., H, W., & S, O.J. (2026). Pre-Deployment Evaluation of a Remote Service for Short-Axis Cardiac MRI Segmentation.. Studies in health technology and informatics. https://doi.org/10.3233/SHTI260788
SH C, H W, S OJ. Pre-Deployment Evaluation of a Remote Service for Short-Axis Cardiac MRI Segmentation.. Studies in health technology and informatics. 2026; doi: 10.3233/SHTI260788
SH C, H W, S OJ. Pre-Deployment Evaluation of a Remote Service for Short-Axis Cardiac MRI Segmentation.[J]. Studies in health technology and informatics. 2026. DOI: 10.3233/SHTI260788.
@article{sh2026,
author = {Chowdhury SH and Winther H and Oeltze-Jafra S},
title = {Pre-Deployment Evaluation of a Remote Service for Short-Axis Cardiac MRI Segmentation.},
journal = {Studies in health technology and informatics},
year = {2026},
doi = {10.3233/SHTI260788},
note = {PMID: 42393950},
}
TY - JOUR AU - Chowdhury SH AU - Winther H AU - Oeltze-Jafra S TI - Pre-Deployment Evaluation of a Remote Service for Short-Axis Cardiac MRI Segmentation. T2 - Studies in health technology and informatics PY - 2026 DO - 10.3233/SHTI260788 AN - PMID:42393950 ER -
Deploying cardiac segmentation models as remote inference services creates a black-box setting in which robustness under out-of-distribution shift is critical. We evaluated two candidate configurations for biventricular segmentation of short-axis cine cardiac magnetic resonance images trained on the same public benchmark dataset: a nnU-Net ensemble and nnSAM. Both were assessed within the same deployment-oriented framework on two external cohorts, a multi-site, multi-vendor adult dataset and a single-site, multi-scanner pediatric congenital heart disease dataset. Performance was evaluated using geometric metrics and biomarker-based endpoints, including clinically relevant ejection fraction (EF) failure rates. While performance was similar in the adult cohort, the nnU-Net ensemble was more robust in the pediatric cohort, with better geometric preservation and lower EF failure rates. These findings indicate that deployment-oriented validation of remote cardiac segmentation services should assess biomarker reliability alongside geometric accuracy.