Calibration Method of Projectional Geometry for X-ray C-arm Fluoroscopy Using Sinogram Data
Source abstract
Abstract
X-ray imaging represents the most commonly used imaging modality in X-ray-guided vascular intervention procedures. Computed tomography (CT) data ensure that the procedure is performed accurately and safely by providing medical staff with positional information of the body part before starting the procedure. In particular, accurate geometric information of the imaging equipment is essential to accurately calculate the three-dimensional (3D) position of catheters used in delicate operations. However, it is difficult to gather this information before surgery. Therefore, this study proposes a novel calibration method that can be used immediately before a procedure and can guarantee the stability of the procedure. The calibration was performed without additional radiography using sinogram data obtained during the 3D CT imaging process, and both the accuracy and calculation time available in the vascular intervention theater were allowable. The experimental results show that the best angular conditions in terms of calculations and accuracy are between −40 and 40 degrees in angular range and 1.6 degrees in angular interval. Consequently, we achieved a calculation time of 2.92 s and an average accuracy of 0.36 mm, thus meeting our goal of accuracy below 1 mm within a minute of computational time.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Anatomy and Medical Technology · Medical Imaging Techniques and Applications · Image and Object Detection Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Biomedical Engineering, School of Electrical Engineering, University of Ulsan, Ulsan 44610, Korea
Funding
University of Ulsan
References (15)
Show source-provided references
1. Image-guidance for surgical procedures10.1088/0031-9155/51/14/R01 ↗
2. Image-guided surgical navigation in otology10.1002/lary.23522 ↗
3. Song, H.S., Woo, J.H., Won, J.Y., and Yi, B.J. (2021). In Vivo Usability Test of Vascular Intervention Robotic System Controlled by Two Types of Master Devices. Appl. Sci., 11.10.3390/app11125453 ↗
4. Geometry calibration between X-ray source and detector for tomosynthesis with a portable X-ray system10.1007/s11548-017-1557-x ↗
5. Estimation of CT cone-beam geometry using a novel method insensitive to phantom fabrication inaccuracy: Implications for isocenter localization accuracy10.1118/1.3589130 ↗
6. A phantom-based calibration method for digital x-ray tomosynthesis
7. A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system10.1080/10589759.2020.1774580 ↗
8. CAD-based X-ray CT calibration and error compensation10.1088/1361-6501/ac5133 ↗
9. A paddle-wheel phantom for geometric calibration of cone-beam CT with offset detector
10. Calculating the Singular Values and Pseudo-Inverse of a Matrix10.1137/0702016 ↗
11. Applications of singular-value decomposition (SVD)10.1016/j.matcom.2004.05.005 ↗
12. A survey on image segmentation10.1016/0031-3203(81)90028-5 ↗
13. Generalizing the Hough transform to detect arbitrary shapes10.1016/0031-3203(81)90009-1 ↗
14. Topological structural analysis of digitized binary images by border following10.1016/0734-189X(85)90016-7 ↗
15. Determining the minimum-area encasing rectangle for an arbitrary closed curve10.1145/360881.360919 ↗