Automatic pelvic fracture segmentation: a deep learning approach and benchmark dataset

Automatic pelvic fracture segmentation: a deep learning approach and benchmark dataset

IntroductionAccurate segmentation of pelvic fractures from computed tomography (CT) is crucial for trauma diagnosis and image-guided reduction surgery. The traditional manual slice-by-slice segmentation by surgeons is time-consuming, experience-dependent, and error-prone. The complex anatomy of the...

Full description

Saved in:
Bibliographic Details
Main Authors: Yanzhen Liu, Sutuke Yibulayimu, Gang Zhu, Chao Shi, Chendi Liang, Chunpeng Zhao, Xinbao Wu, Yudi Sang, Yu Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Medicine
Subjects:
CT segmentation
deep learning
pelvic fracture
reduction planning
image-guided surgery
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1511487/full
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2025.1511487/full

Similar Items