HKA-Net: clinically-adapted deep learning for automated measurement of hip-knee-ankle angle on lower limb radiography for knee osteoarthritis assessment

HKA-Net: clinically-adapted deep learning for automated measurement of hip-knee-ankle angle on lower limb radiography for knee osteoarthritis assessment

Abstract Background Accurate measurement of the hip-knee-ankle (HKA) angle is essential for informed clinical decision-making in the management of knee osteoarthritis (OA). Knee OA is commonly associated with varus deformity, where the alignment of the knee shifts medially, leading to increased stre...

Полное описание

Библиографические подробности
Главные авторы: Young-Tak Kim, Beom-Su Han, Jung Bin Kim, Jason K. Sa, Je Hyeong Hong, Yunsik Son, Jae-Ho Han, Synho Do, Ji Seon Chae, Jung-Kwon Bae
Формат: Статья
Язык:English
Опубликовано: BMC 2024-11-01
Серии:Journal of Orthopaedic Surgery and Research
Предметы:
Hip-knee-ankle angle
Deep learning
Residual network
Varus deformity
Knee osteoarthritis
Lower limb scanogram
Online-ссылка:https://doi.org/10.1186/s13018-024-05265-y

Internet

https://doi.org/10.1186/s13018-024-05265-y

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