Automated segmentation of the lacrimal gland on non-contrast versus post-contrast T1-weighted MRI sequences
Rattachement africain : us. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Purpose The lacrimal glands are small orbital exocrine structures responsible for tear production. Segmentation on MRI is challenging due to their small size, low contrast with adjacent tissues, and partial representation across slices. This study evaluates U-Net based models for automated lacrimal gland segmentation on non-contrast T1-weighted (AX-T1) and contrast-enhanced fat-suppressed (POST-AX-T1-FS) MRI. Methods Eighty-six patients with high-resolution orbital MRI were retrospectively analyzed. Manual gland annotations were created in 3D Slicer. A U-Net architecture was trained with 4-fold cross-validation on an 80:20 train-test split. Performance was assessed on a hold-out set using Dice Similarity Coefficient (DSC), Intersection over Union (IoU), and Hausdorff Distance. Results POST-AX-T1-FS achieved the highest performance (mean DSC 0.79 ± 0.19, IoU 0.68 ± 0.19), outperforming AX-T1. Volume correlation with ground truth was 0.81 for POST-AX-T1-FS and 0.71 for AX-T1. Most errors were false negatives in abnormal gland morphology. Qualitative review showed anatomically consistent segmentations, especially with region-prioritized sampling. Conclusion CNN-based models show ability to segment lacrimal glands from orbital MRI, though performance is moderate with Dice scores around 0.79. Non-contrast sequences may provide reasonably accurate segmentations, but further refinement and broader validation are required. With continued optimization and larger, more diverse datasets, these models may eventually support more consistent gland delineation in research and early exploratory clinical use.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Automated segmentation of the lacrimal gland on non-contrast versus post-contrast T1-weighted MRI sequences
- Date Crossref
- 08/01/2026
- Éditeur
- Frontiers Media SA
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Rensselaer Polytechnic Institute Department of Biology pays non établi dans la noticeUniversité ou école supérieure
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University of Chicago Biological Sciences Division pays non établi dans la noticeUniversité ou école supérieure
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University of Missouri–Kansas City pays non établi dans la noticeUniversité ou école supérieure
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University of Illinois Chicago pays non établi dans la noticeUniversité ou école supérieure
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University of Missouri-Kansas City School of Medicine pays non établi dans la noticeUniversité ou école supérieure
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University of Illinois at Chicago College of Medicine pays non établi dans la noticeUniversité ou école supérieure
Department of Biology — Rensselaer Polytechnic Institute, Biological Sciences Division — University of Chicago et University of Missouri–Kansas City, avec 3 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.