Fig. 2 | Scientific Reports

Fig. 2

From: Clinical validation of a deep learning tool for characterizing spinopelvic mobility in total hip arthroplasty

Fig. 2

Flow diagram illustrating the deep learning pipeline for analyzing functional lateral X-ray images. X-rays are processed using a vision transformer (ViT) model for image classification. For pelvis landmark detection, a convolutional neural network (CNN) is applied directly to identify key landmarks in isolation. For lumbar landmark detection, the YOLOv8 (You Only Look Once, version 8) model is first used to isolate individual vertebrae as tiles. The L5 tile is processed by the CNN to accurately detect lumbar landmarks. Finally, the landmarks are used to calculate PT, SS and LLA.

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