Image Perception, Observer Performance, and Technology Assessment

Bayesian framework inspired no-reference region-of-interest quality measure for brain MRI images

[+] Author Affiliations
Michael Osadebey

NeuroRx Research Inc., MRI Reader Group, Montreal, Québec, Canada

Marius Pedersen

Norwegian University of Science and Technology, Department of Computer Science, Gjøvik, Norway

Douglas Arnold

NeuroRx Research Inc., Montreal, Québec, Canada

Katrina Wendel-Mitoraj

BrainCare Oy, Tampere, Finland

J. Med. Imag. 4(2), 025504 (Jun 13, 2017). doi:10.1117/1.JMI.4.2.025504
History: Received June 11, 2016; Accepted May 16, 2017
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Abstract.  We describe a postacquisition, attribute-based quality assessment method for brain magnetic resonance imaging (MRI) images. It is based on the application of Bayes theory to the relationship between entropy and image quality attributes. The entropy feature image of a slice is segmented into low- and high-entropy regions. For each entropy region, there are three separate observations of contrast, standard deviation, and sharpness quality attributes. A quality index for a quality attribute is the posterior probability of an entropy region given any corresponding region in a feature image where quality attribute is observed. Prior belief in each entropy region is determined from normalized total clique potential (TCP) energy of the slice. For TCP below the predefined threshold, the prior probability for a region is determined by deviation of its percentage composition in the slice from a standard normal distribution built from 250 MRI volume data provided by Alzheimer’s Disease Neuroimaging Initiative. For TCP above the threshold, the prior is computed using a mathematical model that describes the TCP–noise level relationship in brain MRI images. Our proposed method assesses the image quality of each entropy region and the global image. Experimental results demonstrate good correlation with subjective opinions of radiologists for different types and levels of quality distortions.

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© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

Michael Osadebey ; Marius Pedersen ; Douglas Arnold ; Katrina Wendel-Mitoraj and
"Bayesian framework inspired no-reference region-of-interest quality measure for brain MRI images", J. Med. Imag. 4(2), 025504 (Jun 13, 2017). ; http://dx.doi.org/10.1117/1.JMI.4.2.025504


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