The spatial statistics of structural magnetic resonance images: application to post-acquisition quality assessment of brain MRI images

ABSTRACT

This report describes a new quality evaluation method for structural magnetic resonance images (MRI) of the brain. Pixels in MRI images are regarded as regionalized random variables that exhibit distinct and organized geographic patterns. We extract geo-spatial local entropy features and build three separate Gaussian distributed quality models upon them using 250 brain MRI images of different subjects. The MRI images were provided by Alzheimer's disease neuroimaging initiative (ADNI). Image quality of a test image is predicted in a three-step process. In the first step, three separate geo-spatial feature vectors are extracted. The second step standardizes each quality model using corresponding geo-spatial feature vector extracted from the test image. The third step computes image quality by transforming the standardized score to probability. The proposed method was evaluated on images without perceived distortion and images degraded by different levels of motion blur and Rician noise as well as images with different configurations of bias fields. Based on the performance evaluation, our proposed method will be suitable for use in the field of clinical research where quality evaluation is required for the brain MRI images acquired from different MRI scanners and different clinical trial sites before they are fed into automated image processing and image analysis systems.

KEYWORDS:

• Magnetic resonance imaging
• image quality
• whole brain angular segment pixel density
• transverse segment pixel density
• whole brain pixel density and Gaussian distribution

Acknowledgments

ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann- La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health(www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.

Marius Pedersen was supported by the Research Council of Norway, project no. 247689 IQMED: Image Quality enhancement in MEDical diagnosis, monitoring and treatment.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on Contributors

M. E. Osadebey obtained a master's degree with distinction in biomedical engineering from Tampere University of Technology, Finland in 2009 and a Ph.D. in engineering and computer science from Concordia University, Montreal, Canada in 2015. His Ph.D. study focused on the processing of MRI images of the brain. Michael is an MRI reader at NeuroRx Research Inc, a Montreal-based clinical research organization. Michael Osadebey duties at NeuroRx include application of advanced image analysis software in the reading of MRI data of neurological diseases patients undergoing clinical trial drug treatment.

Marius Pedersen received his bachelor's degree in Computer Engineering in 2006, and MiT in Media Technology in 2007, both from Gjovik University College, Norway. He completed a Ph.D. program in colour imaging in 2011 from the University of Oslo, Norway, sponsored by Oce. He is currently employed as an associate professor at NTNU Gjovik, Norway. He is also the director of the Norwegian Colour and Visual Computing Laboratory (Colourlab). His work is centred on subjective and objective image quality.

Douglas Arnold is the Director of Magnetic Resonance Spectroscopy Lab, McGill University, Montreal, Canada and the President/CEO of NeuroRx research Inc., a Montreal-based clinical research organization. Arnold is a neurologist with special expertise in MRI. His personal research interests are centred on the use of advanced neuro-imaging techniques to assess the pathological evolution of multiple sclerosis and Alzheimer's disease and to quantify the effects of therapy on these diseases.

Katrina Wendel-Mitoraj obtained her Ph.D. in biomedical engineering from Tampere University of Technology in 2010. Her Ph.D. study focused on electroencephalography (EEG) electrode sensitivity distributions. Katrina is the CEO and founder of BrainCare Oy. BrainCare Oy (http://braincare.fi/) is a Tampere University of Technology spin-off company founded in 2013 to deliver personalized solutions to improve the quality of life of epilepsy patients. The organization recently concluded clinical trials for a novel mobile application and supporting solutions for long-term monitoring for epileptic patients.

Additional information

Funding

Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). Norges Forskningsråd (247689).