Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/12758
Title: Restoration of Bi-Contrast MRI Data for Intensity Uniformity with Bayesian Coring of Co-Occurrence Statistics
Authors: Hadjidemetriou, Stathis 
Psychogios, Marios Nikos 
Lingor, Paul 
Von Eckardstein, Kajetan 
Papageorgiou, Ismini 
Major Field of Science: Natural Sciences
Field Category: Computer and Information Sciences
Keywords: Bi-contrast MRI intensity restoration;MRI bias field correction;Joint co-occurrence statistics;Non-stationary restoration;Bayesian coring;Van Cittert deconvolution
Issue Date: Dec-2017
Source: Journal of Imaging, 2017, vol. 3, no. 4
Volume: 3
Issue: 4
Journal: Journal of Imaging 
Abstract: The reconstruction of MRI data assumes a uniform radio-frequency field. However, in practice, the radio-frequency field is inhomogeneous and leads to anatomically inconsequential intensity non-uniformities across an image. An anatomic region can be imaged with multiple contrasts reconstructed independently and be suffering from different non-uniformities. These artifacts can complicate the further automated analysis of the images. A method is presented for the joint intensity uniformity restoration of two such images. The effect of the intensity distortion on the auto-co-occurrence statistics of each image as well as on the joint-co-occurrence statistics of the two images is modeled and used for their non-stationary restoration followed by their back-projection to the images. Several constraints that ensure a stable restoration are also imposed. Moreover, the method considers the inevitable differences between the signal regions of the two images. The method has been evaluated extensively with BrainWeb phantom brain data as well as with brain anatomic data from the Human Connectome Project (HCP) and with data of Parkinson's disease patients. The performance of the proposed method has been compared with that of the N4ITK tool. The proposed method increases tissues contrast at least 4.62 times more than the N4ITK tool for the BrainWeb images. The dynamic range with the N4ITK method for the same images is increased by up to +29.77%, whereas, for the proposed method, it has a corresponding limited decrease of -1.15%, as expected. The validation has demonstrated the accuracy and stability of the proposed method and hence its ability to reduce the requirements for additional calibration scans.
ISSN: 2313-433X
DOI: 10.3390/jimaging3040067
Rights: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
Type: Article
Affiliation : Cyprus University of Technology 
University of Gottingen 
Friedrich Schiller University of Jena 
Suedharz Hospital Nordhausen 
Appears in Collections:Άρθρα/Articles

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