Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographs

OBJECTIVE: To identify the feasibility of using a deep convolutional neural network (DCNN) for the detection and localization of hip fractures on plain frontal pelvic radiographs (PXRs). SUMMARY OF BACKGROUND DATA: Hip fracture is a leading worldwide health problem for the elderly. A missed diagnosi...

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Detalles Bibliográficos
Autores principales: Cheng, Chi-Tung, Ho, Tsung-Ying, Lee, Tao-Yi, Chang, Chih-Chen, Chou, Ching-Cheng, Chen, Chih-Chi, Chung, I-Fang, Liao, Chien-Hung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2019
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717182/
https://www.ncbi.nlm.nih.gov/pubmed/30937588
http://dx.doi.org/10.1007/s00330-019-06167-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717182/
https://www.ncbi.nlm.nih.gov/pubmed/30937588
http://dx.doi.org/10.1007/s00330-019-06167-y

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