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Feasibility of a deep learning-based method for automated localization of pelvic floor landmarks using stress MR images
INTRODUCTION AND HYPOTHESIS: Magnetic resonance (MR) imaging plays an important role in assessing pelvic organ prolapse (POP), and automated pelvic floor landmark localization potentially accelerates MR-based measurements of POP. We herein aimed to develop and evaluate a deep learning-based techniqu...
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| I publikationen: | Int Urogynecol J |
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| Huvudupphovsmän: | , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
2021
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8292443/ https://ncbi.nlm.nih.gov/pubmed/33475815 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00192-020-04626-5 |
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