Abstract #2513
An improved complex image combination algorithm for SEMAC
Daehyun Yoon 1 and Brian A Hargreaves 1
1
Radiology, Stanford University, Palo Alto,
CA, United States
A denoising algorithm to improve complex summation of
spectral images for Slice Encoding for Metal Artifact
Correction (SEMAC) sequence is presented. In SEMAC,
multiple spectral images are collected, and combined
together to image spins with a huge resonance frequency
variation around metallic implants. The complex
summation has not been often used for combining these
spectral images because of a serious SNR degradation
even though its image sharpness around the metal is
better than other combination methods. Here we introduce
a new image combination algorithm to improve the SNR for
the complex summation to provide both sharpness and high
SNR.
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