Harnessing ResNet50 and SENet for enhanced ankle fracture identification

Harnessing ResNet50 and SENet for enhanced ankle fracture identification

Abstract Background Ankle fractures are prevalent injuries that necessitate precise diagnostic tools. Traditional diagnostic methods have limitations that can be addressed using machine learning techniques, with the potential to improve accuracy and expedite diagnoses. Methods We trained various dee...

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Bibliographic Details
Main Authors: Hua Wang, Jichong Ying, Jianlei Liu, Tianming Yu, Dichao Huang
Format: Article
Language:English
Published: BMC 2024-04-01
Series:BMC Musculoskeletal Disorders
Subjects:
Ankle fractures
Deep learning
ResNet50
SENet
Radiographic images
Grad-CAM
Online Access:https://doi.org/10.1186/s12891-024-07355-8

Internet

https://doi.org/10.1186/s12891-024-07355-8

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