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Spectral CT Algorithms

Spectral CT Algorithms

Abstract

Spectral CT algorithms generally target two different tasks: On one hand, it is of interest to distinguish between two materials that yield the same range of CT numbers in a standard CT image. Two or more spectral CT measurement channels with distinct spectral weightings often yield an improved segmentation between the two materials, both in a visual assessment and in a computational segmentation algorithm. The separation of bone and blood mixed with iodine contrast media is a prominent clinical example. On the other hand, spectral CT data follow well-known physical attenuation rules. In many cases, the measurement process description can be inverted to yield quantitative material information, e.g., concentrations or atomic number information of the material constituents. In this chapter, we summarize the main algorithms dedicated to this target of spectral CT imaging.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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