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.
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2023-01-01
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| Series: | Insights into Imaging |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13244-022-01342-0 |
| _version_ | 1797958629988499456 |
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| author | Maike Theis Tolga Tonguc Oleksandr Savchenko Sebastian Nowak Wolfgang Block Florian Recker Markus Essler Alexander Mustea Ulrike Attenberger Milka Marinova Alois M. Sprinkart |
| author_facet | Maike Theis Tolga Tonguc Oleksandr Savchenko Sebastian Nowak Wolfgang Block Florian Recker Markus Essler Alexander Mustea Ulrike Attenberger Milka Marinova Alois M. Sprinkart |
| author_sort | Maike Theis |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T00:21:40Z |
| format | Article |
| id | doaj.art-39b4b48d98ed4b6dbc34f182d097e7b4 |
| institution | Directory Open Access Journal |
| issn | 1869-4101 |
| language | English |
| last_indexed | 2024-04-11T00:21:40Z |
| publishDate | 2023-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Insights into Imaging |
| spelling | doaj.art-39b4b48d98ed4b6dbc34f182d097e7b42023-01-08T12:13:50ZengSpringerOpenInsights into Imaging1869-41012023-01-011411910.1186/s13244-022-01342-0Deep learning enables automated MRI-based estimation of uterine volume also in patients with uterine fibroids undergoing high-intensity focused ultrasound therapyMaike Theis0Tolga Tonguc1Oleksandr Savchenko2Sebastian Nowak3Wolfgang Block4Florian Recker5Markus Essler6Alexander Mustea7Ulrike Attenberger8Milka Marinova9Alois M. Sprinkart10Department of Diagnostic and Interventional Radiology, University Hospital BonnDepartment of Diagnostic and Interventional Radiology, University Hospital BonnDepartment of Diagnostic and Interventional Radiology, University Hospital BonnDepartment of Diagnostic and Interventional Radiology, University Hospital BonnDepartment of Diagnostic and Interventional Radiology, University Hospital BonnDepartment of Gynaecology and Gynaecological Oncology, University Hospital BonnDepartment of Nuclear Medicine, University Hospital BonnDepartment of Gynaecology and Gynaecological Oncology, University Hospital BonnDepartment of Diagnostic and Interventional Radiology, University Hospital BonnDepartment of Diagnostic and Interventional Radiology, University Hospital BonnDepartment of Diagnostic and Interventional Radiology, University Hospital BonnKey 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.https://doi.org/10.1186/s13244-022-01342-0Deep learningMagnetic resonance imagingUterusLeiomyoma |
| spellingShingle | Maike Theis Tolga Tonguc Oleksandr Savchenko Sebastian Nowak Wolfgang Block Florian Recker Markus Essler Alexander Mustea Ulrike Attenberger Milka Marinova Alois M. Sprinkart Deep learning enables automated MRI-based estimation of uterine volume also in patients with uterine fibroids undergoing high-intensity focused ultrasound therapy Insights into Imaging Deep learning Magnetic resonance imaging Uterus Leiomyoma |
| title | Deep learning enables automated MRI-based estimation of uterine volume also in patients with uterine fibroids undergoing high-intensity focused ultrasound therapy |
| title_full | Deep learning enables automated MRI-based estimation of uterine volume also in patients with uterine fibroids undergoing high-intensity focused ultrasound therapy |
| title_fullStr | Deep learning enables automated MRI-based estimation of uterine volume also in patients with uterine fibroids undergoing high-intensity focused ultrasound therapy |
| title_full_unstemmed | Deep learning enables automated MRI-based estimation of uterine volume also in patients with uterine fibroids undergoing high-intensity focused ultrasound therapy |
| title_short | Deep learning enables automated MRI-based estimation of uterine volume also in patients with uterine fibroids undergoing high-intensity focused ultrasound therapy |
| title_sort | deep learning enables automated mri based estimation of uterine volume also in patients with uterine fibroids undergoing high intensity focused ultrasound therapy |
| topic | Deep learning Magnetic resonance imaging Uterus Leiomyoma |
| url | https://doi.org/10.1186/s13244-022-01342-0 |
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