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AN IMPROVED QUALITY GUIDED PHASE UNWRAPPING METHOD AND ITS APPLICATIONS TO MRI
Author(s) -
Yudong Zhang,
Shuihua Wang‎,
Genlin Ji,
Zhengchao Dong
Publication year - 2014
Publication title -
electromagnetic waves
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 89
eISSN - 1559-8985
pISSN - 1070-4698
DOI - 10.2528/pier14021005
Subject(s) - computation , computer science , norm (philosophy) , variance (accounting) , algorithm , quality (philosophy) , phase (matter) , artificial intelligence , physics , accounting , political science , law , business , quantum mechanics
An improved method of quality guided phase unwrapping (QGPU) is proposed in this work. It extracts the quality map via a median flltered phase derivative variance (MFPDV) that applies a two-dimensional median fllter on the phase derivative variance (PDV) map, in order to reduce the efiect of noise in the background area. In addition, we employed the Indexed Interwoven Linked List (I2L2) structure to store the orderly adjoin list more e-ciently and the Two Section Guided Strategy (TSGS) to reduce comparison frequency. The experiments demonstrate that the normalized L1 norm of MFPDV of a brain MR image is only 0.0827, less than that of PDV method at 0.0923. Besides, the computation time of QGPU with I2L2 technique is only 30% of that with sequence structure, and the computation time of QGPU with TSGS is only 65% of that without TSGS. In total, the proposed MFPDV upwrap phase images better than conventional PDV map, and I2L2 and TSGS are e-cient strategies to reduce computation time.

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