LSNet: a novel CNN architecture to identify wrist fracture from a small X-ray dataset-Reference-Cited by-同舟云学术

LSNet: a novel CNN architecture to identify wrist fracture from a small X-ray dataset

Published:2023-06 Issue:5 Volume:15 Page:2469-2477
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Anwar Talha,Anwar Hassan

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s41870-023-01311-w.pdf

Reference29 articles.

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3. Cheng CT, Ho TY, Lee TY et al (2019) Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographs. Eur Radiol 29(10):5469–5477

4. Crowe CS, Massenburg BB, Morrison SD et al (2020) Global trends of hand and wrist trauma: a systematic analysis of fracture and digit amputation using the global burden of disease 2017 study. Inj Prev 26(Suppl 2):i115–i124

5. Ebsim R, Naqvi J, Cootes T (2017) Fully automatic detection of distal radius fractures from posteroanterior and lateral radiographs. In: Cardoso M. J. (ed) Computer assisted and robotic endoscopy and clinical image-based procedures. Springer, 91–98 https://doi.org/10.1007/978-3-319-67543-5_8

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