Paper
12 May 2004 Reconstruction with most likely trajectory for proton computed tomography
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Abstract
Advantages of proton computed tomography (pCT) have been recognized in the past decades. However, the quality of pCT images is limited due to the stochastic nature of the proton path inside the object. Numerous small angle scatters by the nuclei Coulomb field cause the exact proton path impossible to trace. The reconstruction from measurements of the proton energy-loss has a spatial resolution limit due to these deflections. However, it has been shown that the proton path inside a uniform medium follows certain probability distribution so that a most likely trajectory (MLT) can be derived analytically for each proton. For real scan of a regular non-uniform object in pCT, the internal trajectory is better approximated by the MLT rather than a straight-line estimation. In this report, we presented preliminary studies on how the curved trajectories would affect the quality of the reconstructed images, and how much improvement we can achieve in reconstruction with the exact trajectory information. Analytical simulations with three phantoms, including a uniform disk phantom, multi-hole Aluminum phantom and Shepp-Logan phantom, were performed using artificial internal trajectories calculated based on the entrance and exit proton information. Reconstructions with the exact paths were compared to those with the straight-line path estimation. Significant improvement in density uniformity and spatial resolution were observed in the reconstructions with the path information.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tianfang Li and Jerome Zhengrong Liang "Reconstruction with most likely trajectory for proton computed tomography", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); https://doi.org/10.1117/12.535811
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Cited by 9 scholarly publications and 4 patents.
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KEYWORDS
Computed tomography

Reconstruction algorithms

Aluminum

Spatial resolution

Image resolution

Particles

Sensors

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