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Title of Journal: Int J CARS

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Abbravation: International Journal of Computer Assisted Radiology and Surgery

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Springer Berlin Heidelberg

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DOI

10.1016/0304-8853(96)00061-3

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1861-6429

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Scaling calibration in region of interest reconstr

Authors: Yan Xia Frank Dennerlein Sebastian Bauer Hannes Hofmann Joachim Hornegger Andreas Maier
Publish Date: 2014/01/23
Volume: 9, Issue: 3, Pages: 345-356
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Abstract

   Recently a reconstruction algorithm for region of interest ROI imaging in Carm CT was published named Approximate Truncation Robust Algorithm for Computed Tomography ATRACT Even in the presence of substantial data truncation the algorithm is able to reconstruct images without the use of explicit extrapolation or prior knowledge However the method suffers from a scaling and offset artifact in the reconstruction Hence the reconstruction results are not quantitative It is our goal to reduce the scaling and offset artifact so that Hounsfield unit HU values can be used for diagnosis   In this paper we investigate two variants of the ATRACT method and present the analytical derivations of these algorithms in the Fourier domain Then we propose an empirical correction measure that can be applied to the ATRACT algorithm to effectively compensate the scaling and offset issue The proposed method is evaluated on ten clinical datasets in the presence of different degrees of artificial truncation   With the proposed correction approach we achieved an average relative rootmeansquare error rRMSE of 281  with respect to nontruncated Feldkamp Davis and Kress reconstruction even for severely truncated data The rRMSE is reduced to as little as 10  of the image reconstructed without the scaling calibration   The reconstruction results show that ROI reconstruction of high accuracy can be achieved since the scaling and offset artifact are effectively eliminated by the proposed method With this improvement the HU values may be used for postprocessing operations such as bone or soft tissue segmentation if some tolerance is acceptedDisclaimer Patient datasets were collected for diagnostic purposes during medical interventions Informed consent was obtained from all patients for scientific use of their data The concepts and information presented in this paper are based on research and are not commercially available


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