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Abstract #4224

Comparison of Wavelet Subband Decomposition Methods for High-Frequency Subband CS

Kyunghyun Sung1, Anderson N. Nnewihe1, 2, Bruce L. Daniel1, Brian A. Hargreaves1

1Radiology, Stanford University, Stanford, CA, United States; 2Bioengineering, Stanford University, Stanford, CA, United States

Compressed sensing (CS) is a technique that allows accurate reconstruction of images from a reduced set of acquired data. Here, we describe two wavelet subband decomposition methods for High-frequency Subband CS, which enable to employ selective application of different undersampling patterns and reconstructions in different k-space regions. Two wavelet decomposition methods are evaluated in high-resolution T1- and T2-weighted 3D breast imaging with extremely high acceleration factors.