Scale- and Slice-aware Net (S
MRI segmentation
convolutional neural networks
multislice feature fusion
organs and musculoskeletal structures in the female pelvis
parallel scale-aware module
Journal
Magnetic resonance in medicine
ISSN: 1522-2594
Titre abrégé: Magn Reson Med
Pays: United States
ID NLM: 8505245
Informations de publication
Date de publication:
01 2022
01 2022
Historique:
revised:
11
06
2021
received:
20
01
2021
accepted:
04
07
2021
pubmed:
3
8
2021
medline:
1
2
2022
entrez:
2
8
2021
Statut:
ppublish
Résumé
MRI of organs and musculoskeletal structures in the female pelvis presents a unique display of pelvic anatomy. Automated segmentation of pelvic structures plays an important role in personalized diagnosis and treatment on pelvic structures disease. Pelvic organ systems are very complicated, and it is a challenging task for 3D segmentation of massive pelvic structures on MRI. A new Scale- and Slice-aware Net ( Experiments have been performed on a pelvic MRI cohort of 27 MR images from 27 patient cases. Across the cohort and 54 categories of organs and musculoskeletal structures manually delineated, The experimental results on the pelvic 3D MR dataset show that the proposed
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
431-445Informations de copyright
© 2021 International Society for Magnetic Resonance in Medicine.
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