RGB-D/CT Registration for Preemptive Patient Pose Alignment in Longitudinal CT Scans
4 affiliations
- 1Chair for Computer Aided Medical Procedures and Augmented Reality, Technical University of Munich,Munich, Germany
- 2Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Augsburg, Augsburg, Germany / Digital Medicine, University Hospital Augsburg, Augsburg, Germany / Bavarian Center for Cancer Research (BZKF),Augsburg, Germany
- 3Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Augsburg,Augsburg, Germany
- 4Chair for Computer Aided Medical Procedures and Augmented Reality, Technical University of Munich, Munich, Germany / Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Augsburg, Augsburg, Germany / Digital Medicine, University Hospital Augsburg, Augsburg, Germany / Bavarian Center for Cancer Research (BZKF),Augsburg, Germany
Abstract
Registration of longitudinal Computed Tomography (CT) scans is critical for monitoring treatment responses, yet its precision is often compromised by inconsistencies in patient positioning between sessions. Historically, the medical imaging community has relied purely on post-hoc ("postscan") image registration to correct these inconsistencies [1]. Whether utilizing rigid or deformable models, post-hoc registration is a reactive tool applied to data that is inherently flawed at acquisition. This work proposes a paradigm shift: addressing variability at its source through pre-scan patient pose alignment. By capturing the patient’s current pose with an integrated RGB-D camera prior to the follow-up CT scan, discrepancies relative to a baseline CT scan can be registered and visualized. This paper outlines an articulated registration pipeline designed to overcome the domain gap between occluded RGB-D surface data and volumetric CT data. The torso serves as a rigid anchor to align the modalities, after which individual limbs undergo local point-to-plane Iterative Closest Point refinement. The spatial corrections are then projected onto the original 2D RGB image, providing intuitive visual guidance for clinical staff. Validated on an anthropomorphic phantom, our pipeline demonstrates highly stable torso anchoring (average centroid error over 10 iterations: 2.69 cm) and consistent limb alignment (mean surface error: 1.61-1.84 cm). This proof-of-concept establishes a foundation for proactive patient alignment in longitudinal imaging.
Related
- Performance of five large language models in frozen shoulder patient education: a multidimensional evaluation of readability, quality, clinical alignment, and safety
- Longitudinal Changes in Self-Esteem and Evaluation of Patient Satisfaction After Keratopigmentation for Unilateral Corneal Opacity
- Longitudinal Dynamic MRI Through Multisession Joint Reconstruction Incorporating Patient-Specific Prior Image Information
- Three-Year Functional Vision, Longitudinal Refractive Outcomes, and Patient-Reported Outcomes After Bilateral Implantation of the Extend Bessel-Optics Intraocular Lens: An Independent Real-World Ambispective Study
- Association of depression and epilepsy in rural northern Rwanda: a prospective longitudinal study with a patient-centered approach
BibTeX
@article{elisabeth2026rgbdct,
title = {{RGB-D/CT Registration for Preemptive Patient Pose Alignment in Longitudinal CT Scans}},
author = {Schiele Elisabeth and Wördehoff Melina and Decker Josua A. and Förner Lukas and Wendler Thomas},
journal = {Current Directions in Biomedical Engineering},
year = {2026},
month = oct,
doi = {10.1515/cdbme-2026-0217},
url = {https://doi.org/10.1515/cdbme-2026-0217},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - RGB-D/CT Registration for Preemptive Patient Pose Alignment in Longitudinal CT Scans
AU - Schiele Elisabeth
AU - Wördehoff Melina
AU - Decker Josua A.
AU - Förner Lukas
AU - Wendler Thomas
PY - 2026
DA - 2026/10/26
JO - Current Directions in Biomedical Engineering
DO - 10.1515/cdbme-2026-0217
UR - https://doi.org/10.1515/cdbme-2026-0217
AB - Registration of longitudinal Computed Tomography (CT) scans is critical for monitoring treatment responses, yet its precision is often compromised by inconsistencies in patient positioning between sessions. Historically, the medical imaging community has relied purely on post-hoc ("postscan") image registration to correct these inconsistencies [1]. Whether utilizing rigid or deformable models, post-hoc registration is a reactive tool applied to data that is inherently flawed at acquisition. This work proposes a paradigm shift: addressing variability at its source through pre-scan patient pose alignment. By capturing the patient’s current pose with an integrated RGB-D camera prior to the follow-up CT scan, discrepancies relative to a baseline CT scan can be registered and visualized. This paper outlines an articulated registration pipeline designed to overcome the domain gap between occluded RGB-D surface data and volumetric CT data. The torso serves as a rigid anchor to align the modalities, after which individual limbs undergo local point-to-plane Iterative Closest Point refinement. The spatial corrections are then projected onto the original 2D RGB image, providing intuitive visual guidance for clinical staff. Validated on an anthropomorphic phantom, our pipeline demonstrates highly stable torso anchoring (average centroid error over 10 iterations: 2.69 cm) and consistent limb alignment (mean surface error: 1.61-1.84 cm). This proof-of-concept establishes a foundation for proactive patient alignment in longitudinal imaging.
SN - 2364-5504
ER -