A MAP-MRF filter for phase-sensitive coil combination in autocalibrating partially parallel susceptibility weighted MRI
Sreekanth Madhusoodhanan, Joseph Suresh Paul

TL;DR
This paper introduces a MAP-MRF filter for phase-sensitive coil combination in autocalibrating partially parallel susceptibility weighted MRI, improving CNR by optimizing phase filtering based on local probabilistic weights.
Contribution
The study develops a novel MAP-MRF filtering method that enhances phase combination in SWI, outperforming traditional weighted averaging in CNR improvement.
Findings
Higher CNR in combined phase images with MAP-MRF filter
Reduced noise amplification compared to existing methods
Effective application in both simulated and in vivo SWI data
Abstract
A statistical approach for combination of channel phases is developed for optimizing the Contrast-to-Noise Ratio (CNR) in Susceptibility Weighted Images (SWI) acquired using autocalibrating partially parallel techniques. The unwrapped phase images of each coil are filtered using local random field based probabilistic weights, derived using energy functions representative of noisy sensitivity and tissue information pertaining to venous structure in the individual channel phase images. The channel energy functions are obtained as functions of local image intensities, first or second order clique phase difference and a threshold scaling parameter dependent on the input noise level. Whereas the expectation of the individual energy functions with respect to the noise distribution in clique phase differences is to be maximized for optimal filtering, the expectation of tissue energy function…
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Taxonomy
TopicsAdvanced MRI Techniques and Applications · Medical Imaging Techniques and Applications · NMR spectroscopy and applications
