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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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