Deep learning enables automated MRI-based estimation of uterine volume also in patients with uterine fibroids undergoing high-intensity focused ultrasound therapy

Deep learning enables automated MRI-based estimation of uterine volume also in patients with uterine fibroids undergoing high-intensity focused ultrasound therapy

Key points Deep learning methods enable accurate segmentation of the uterus in T2-weighted MRI. Automatic uterine volumetry is possible in patients with and without leiomyomas. Automated volumetry enables an objective assessment of response to high-intensity focused ultrasound therapy.

Bibliographic Details
Main Authors: Maike Theis, Tolga Tonguc, Oleksandr Savchenko, Sebastian Nowak, Wolfgang Block, Florian Recker, Markus Essler, Alexander Mustea, Ulrike Attenberger, Milka Marinova, Alois M. Sprinkart
Format: Article
Language:English
Published: SpringerOpen 2023-01-01
Series:Insights into Imaging
Subjects:
Deep learning
Magnetic resonance imaging
Uterus
Leiomyoma
Online Access:https://doi.org/10.1186/s13244-022-01342-0
Description
Summary:Key points Deep learning methods enable accurate segmentation of the uterus in T2-weighted MRI. Automatic uterine volumetry is possible in patients with and without leiomyomas. Automated volumetry enables an objective assessment of response to high-intensity focused ultrasound therapy.
ISSN:1869-4101

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