Abstract #2542
A simple and practical method to optimize regularization parameters in Compressed Sensing reconstruction of Time-of-flight (TOF) MR angiography
Koji Fujimoto 1 , Takayuki Yamamoto 1 , Thai Akasaka 1 , Tomohisa Okada 1 , Yasutaka Fushimi 1 , Akira Yamamoto 1 , Toshiyuki Tanaka 2 , Kei Sano 2 , Masayuki Ohzeki 2 , and Kaori Togashi 1
1
Diagnostic Imaging and Nuclear Medicine,
Graduate School of Medicine, Kyoto University, Kyoto,
Kyoto, Japan,
2
Department
of Systems Science, Graduate School of Informatics,
Kyoto University, Kyoto, Kyoto, Japan
Reports on applying Compressed Sensing (CS) to TOF-MRA
is still limited, probably because of difficulty due to
a relatively lower SNR, and is hence challenging. In
this work, we propose a simple and practical method to
select a good regularization parameter applicable to
TOF-MRA image reconstruction. We performed CS with 4x
accelerated data at 3.0T by the FCSA algorithm with
varying weights for Wavelet and Total Variation penalty.
Among 6 different quantitative measures, the image
selected by the highest SSIM value by using a masked MIP
image was considered best by a clinical radiologist’s
evaluation.
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