Paper
22 March 2010 Histogram-driven cupping correction (HDCC) in CT
Y. Kyriakou, M. Meyer, R. Lapp, W. A. Kalender
Author Affiliations +
Abstract
Typical cupping correction methods are pre-processing methods which require either pre-calibration measurements or simulations of standard objects to approximate and correct for beam hardening and scatter. Some of them require the knowledge of spectra, detector characteristics, etc. The aim of this work was to develop a practical histogram-driven cupping correction (HDCC) method to post-process the reconstructed images. We use a polynomial representation of the raw-data generated by forward projection of the reconstructed images; forward and backprojection are performed on graphics processing units (GPU). The coefficients of the polynomial are optimized using a simplex minimization of the joint entropy of the CT image and its gradient. The algorithm was evaluated using simulations and measurements of homogeneous and inhomogeneous phantoms. For the measurements a C-arm flat-detector CT (FD-CT) system with a 30×40 cm2 detector, a kilovoltage on board imager (radiation therapy simulator) and a micro-CT system were used. The algorithm reduced cupping artifacts both in simulations and measurements using a fourth-order polynomial and was in good agreement to the reference. The minimization algorithm required less than 70 iterations to adjust the coefficients only performing a linear combination of basis images, thus executing without time consuming operations. HDCC reduced cupping artifacts without the necessity of pre-calibration or other scan information enabling a retrospective improvement of CT image homogeneity. However, the method can work with other cupping correction algorithms or in a calibration manner, as well.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Y. Kyriakou, M. Meyer, R. Lapp, and W. A. Kalender "Histogram-driven cupping correction (HDCC) in CT", Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 76221S (22 March 2010); https://doi.org/10.1117/12.844206
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KEYWORDS
Computed tomography

Head

Sensors

Calibration

Detection and tracking algorithms

Imaging systems

Computer simulations

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