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access icon free Image reconstruction for emission tomography using intensity normalised patch-based regularisation

Recently, patch-based regularisation methods have been a topic for tomographic reconstruction, since they are expected to preserve features within patches. However, conventional patch-based methods tend to ignore important similarities when the two patches being compared have a large intensity difference, while they share similar features in a scaled domain, which often results in the loss of fine details. In this work, to overcome this problem, the authors measure the similarity using normalised patch (NP) differences as well as unnormalised standard patch (SP) differences. A NP difference is obtained by normalising each patch with respect to its mean value and scaling the difference between the two NPs. The addition of NPs provides great potential to restore non-piecewise flat regions that are often ignored by SP-based regularisation methods. To combine the two types of patch differences, they use a method of space-variant linear combination where the weight controlling the balance between the two types is derived from a transform of the gradient of each pixel location. The authors’ experiments for emission tomography reconstruction demonstrate that the proposed method improves not only the overall reconstruction accuracy for realistic data with the non-piecewise flat structure, but also the contrast recovery of small structures.

http://iet.metastore.ingenta.com/content/journals/10.1049/iet-ipr.2018.5706
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content/journals/10.1049/iet-ipr.2018.5706
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