Paper
12 March 2009 Geometric calibration and distortion calibration for CT from scans of unknown objects using complementary rays
Author Affiliations +
Proceedings Volume 7258, Medical Imaging 2009: Physics of Medical Imaging; 72581Q (2009) https://doi.org/10.1117/12.811652
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
To achieve good image quality for computed tomography, it is important to accurately know the geometrical relationship between the X-ray source, the axis of rotation, and all of the detector channels. This usually involves knowing gross parameters such as iso-ray coordinate, detector pixel pitch, and source-to-detector distance, but for some detector types such as distorted arrays, polygonal or tiled arrays, or arrays of irregularly placed sparse detectors, it is beneficial to measure a more detailed description of the individual channel locations. Typically, geometric calibration and distortion calibration are performed using specialized phantoms, such as a pin, an array of pellets, or a wire grid, but these can have their practical downsides for certain applications. A promising recent alternative is to calibrate geometry in a way that requires no particular phantom or a priori knowledge of the scanned object -- these approaches are particularly helpful for high magnifications, large heavy objects, frequent calibration, and retrospective calibration. However, until now these approaches have only addressed gross geometry. In this paper, a framework is given which allows one to calibrate both gross and fine geometry from unknown objects. Example images demonstrate the success of the proposed methods on both real and simulated data.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kevin M. Holt "Geometric calibration and distortion calibration for CT from scans of unknown objects using complementary rays", Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 72581Q (12 March 2009); https://doi.org/10.1117/12.811652
Lens.org Logo
CITATIONS
Cited by 2 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Calibration

Distortion

Sensors

Scanners

X-ray computed tomography

Image quality

Data modeling

Back to Top