Development and clinical validation of a deep learning-based knee CT image segmentation method for robotic-assisted total knee arthroplasty.

Xingyu LiuSonglin LiXiongfei ZouXi ChenHongjun XuYang YuZhao GuDong LiuRunchao LiYaojiong WuGuangzhi WangHongen LiaoWenwei QianYiling Zhang

Published in: The international journal of medical robotics + computer assisted surgery : MRCAS (2024)

DDA-Transformer exhibited significantly improved accuracy and robustness in knee joint segmentation, and this convenient and stable knee joint CT image segmentation network significantly improved the accuracy of the TKA procedure.

Keyphrases

deep learning
total knee arthroplasty
convolutional neural network
total hip
artificial intelligence
image quality
dual energy
computed tomography
contrast enhanced
machine learning
positron emission tomography
magnetic resonance imaging
minimally invasive
magnetic resonance
network analysis