PreprintAll rights reservedmedRxiv
Automated MRI-Based Segmentation of the Cranio-Cervical Venous System Using a Dedicated Deep Learning Pipeline
- 1Department of Neurosurgery, University Hospital of Brest, Brest, France; Anatomy Department, University of Western Brittany (UBO), Brest, France
Related
- Automatic segmentation of histological zones in rat distraction osteogenesis using a self-configuring deep learning pipeline
- A novel morphological assessment approach for abdominal aortic aneurysms: automated segmentation and measurement using a semi-supervised deep learning algorithm
- Early Detection of Mortality Risk in Preterm Neonates Using a Random Forest Classifier and Tree-Based Pipeline Optimization Tool Automated Machine Learning
- A fully automated machine learning assisted pipeline to predict disease progression for early-stage hypertrophic cardiomyopathy from echocardiography
- Automated morphometric segmentation analysis of hand X-ray image using deep learning network
BibTeX
@misc{duigou2026automated,
title = {{Automated MRI-Based Segmentation of the Cranio-Cervical Venous System Using a Dedicated Deep Learning Pipeline}},
author = {M. Duigou and T. Treguer and B. Dissaux and J. Ognard and R. Seizeur and C. Capel},
howpublished = {medRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.08.26367527},
url = {https://www.medrxiv.org/content/10.64898/2026.11.08.26367527v1},
}
RIS
TY - UNPB
TI - Automated MRI-Based Segmentation of the Cranio-Cervical Venous System Using a Dedicated Deep Learning Pipeline
AU - M. Duigou
AU - T. Treguer
AU - B. Dissaux
AU - J. Ognard
AU - R. Seizeur
AU - C. Capel
PY - 2026
DA - 2026/11/08
PB - medRxiv
DO - 10.64898/2026.11.08.26367527
UR - https://www.medrxiv.org/content/10.64898/2026.11.08.26367527v1
ER -