Automatic annotation of hip anatomy in fluoroscopy for robust and efficient 2D/3D registration

• Published in: International journal for computer assisted radiology and surgery Vol. 15; no. 5; pp. 759 - 769
• Main Authors: Grupp, Robert B., Unberath, Mathias, Gao, Cong, Hegeman, Rachel A., Murphy, Ryan J., Alexander, Clayton P., Otake, Yoshito, McArthur, Benjamin A., Armand, Mehran, Taylor, Russell H.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.05.2020; Springer Nature B.V
• Subjects: Algorithms; Anatomy; Annotations; Computer Imaging; Computer Science; Femur; Femur - diagnostic imaging; Femur - surgery; Fluoroscopic imaging; Fluoroscopy - methods; Ground truth; Health Informatics; Hip; Humans; Image segmentation; Imaging; Imaging, Three-Dimensional - methods; Labels; Medicine; Medicine & Public Health; Neural networks; Neural Networks, Computer; Original Article; Pattern Recognition and Graphics; Pelvis; Pelvis - diagnostic imaging; Pelvis - surgery; Radiology; Registration; Robustness; Surgery; Tomography, X-Ray Computed - methods; Training; Vision; Workflow; 2D/3D registration; Semantic segmentation; X-ray navigation; Landmark detection; Orthopedics

Purpose Fluoroscopy is the standard imaging modality used to guide hip surgery and is therefore a natural sensor for computer-assisted navigation. In order to efficiently solve the complex registration problems presented during navigation, human-assisted annotations of the intraoperative image are t...