Detecting pelvic fracture on 3D-CT using deep convolutional neural networks with multi-orientated slab images

Detecting pelvic fracture on 3D-CT using deep convolutional neural networks with multi-orientated slab images

Abstract Pelvic fracture is one of the leading causes of death in the elderly, carrying a high risk of death within 1 year of fracture. This study proposes an automated method to detect pelvic fractures on 3-dimensional computed tomography (3D-CT). Deep convolutional neural networks (DCNNs) have bee...

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Bibliographic Details
Main Authors: Kazutoshi Ukai, Rashedur Rahman, Naomi Yagi, Keigo Hayashi, Akihiro Maruo, Hirotsugu Muratsu, Syoji Kobashi
Format: Article
Language:English
Published: Nature Publishing Group 2021-06-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-91144-z

Internet

https://doi.org/10.1038/s41598-021-91144-z

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