Fully automated pelvic bone segmentation in multiparameteric MRI using a 3D convolutional neural network

Fully automated pelvic bone segmentation in multiparameteric MRI using a 3D convolutional neural network

Abstract Background Accurate segmentation of pelvic bones is an initial step to achieve accurate detection and localisation of pelvic bone metastases. This study presents a deep learning-based approach for automated segmentation of normal pelvic bony structures in multiparametric magnetic resonance...

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Bibliographic Details
Main Authors: Xiang Liu, Chao Han, He Wang, Jingyun Wu, Yingpu Cui, Xiaodong Zhang, Xiaoying Wang
Format: Article
Language:English
Published: SpringerOpen 2021-07-01
Series:Insights into Imaging
Subjects:
Pelvic bones
Segmentation
Multiparametric magnetic resonance imaging
Convolutional neural network
Deep learning
Online Access:https://doi.org/10.1186/s13244-021-01044-z

Internet

https://doi.org/10.1186/s13244-021-01044-z

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