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Title
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An adaptive probability map for the Discrete Algebraic Reconstruction Technique
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Author
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Abstract
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| The Discrete Algebraic Reconstruction Technique (DART) [1] is a well-known method to reconstruct images from a set of X-ray projections acquired from objects that consist of only a small number of materials. For such materials, DART has been shown to lead to high quality images, even when the number of available projections is small or when the projections are acquired in a limited angular range. The core idea of DART is to reduce the size of the reconstruction problem by iteratively updating only those pixels that are likely to be misclassified. However, DART as proposed in [1] updates the image pixels independent of the material. This paper presents an improved pixel update strategy by introducing a probability map that measures the classification accuracy of each pixel based on its grey value evolution throughout the iterations. Through simulation experiments, we show that, compared to DART, our proposed method either improves upon convergence speed or on quality of the reconstructed image. |
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Language
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English
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Source (journal)
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NDT.net
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Source (book)
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10th Conference on Industrial Computed Tomography (iCT) 2020, 4-7 Feb, Wels, Austria
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Publication
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NDT.net
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2020
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Volume/pages
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02
(2020)
, 10 p.
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Full text (open access)
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