Artificial intelligence assisted assessment of pre- and post-arthroplasty lower limb alignment on long-leg and knee close-up X-rays

5 pages•Published: March 8, 2024

Michel Bonnin, Florian Müller-Fouarge, Théo Estienne, Samir Bekadar, Salvatore Ratano, Yannick Carrillon, Charlotte Pouchy and Tarik Ait Siselmi

Abstract

In this study, we present and evaluate a suite of deep learning algorithms to assist orthopedic surgeons in the analysis of pre- and post-operative lower limb X-ray images. Deep learning algorithms obtained similar results as surgeons on the measurement of 10 different angles used for the assessment of the lower limb alignment.

Keyphrases: artificial intelligence, lower limb alignment, orthopedics

In: Joshua W Giles (editor). Proceedings of The 22nd Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, vol 6, pages 8-12.

Links:	https://easychair.org/publications/paper/Qtdld
	https://doi.org/10.29007/21wn

BibTeX entry

@inproceedings{CAOS2023:Artificial_intelligence_assisted_assessment,
  author    = {Michel Bonnin and Florian Müller-Fouarge and Théo Estienne and Samir Bekadar and Salvatore Ratano and Yannick Carrillon and Charlotte Pouchy and Tarik Ait Siselmi},
  title     = {Artificial intelligence assisted assessment of pre- and post-arthroplasty lower limb alignment on long-leg and knee close-up X-rays},
  booktitle = {Proceedings of The 22nd Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery},
  editor    = {Joshua W Giles},
  series    = {EPiC Series in Health Sciences},
  volume    = {6},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-5305},
  url       = {/publications/paper/Qtdld},
  doi       = {10.29007/21wn},
  pages     = {8-12},
  year      = {2024}}

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