Automated quality assessment of structural magnetic resonance images in children: Comparison with visual inspection and surface-based reconstruction

Author:

White Tonya12ORCID,Jansen Philip R.123,Muetzel Ryan L.13,Sudre Gustavo4,El Marroun Hanan135,Tiemeier Henning156,Qiu Anqi78ORCID,Shaw Philip4,Michael Andrew M.9,Verhulst Frank C.110

Affiliation:

1. Department of Child and Adolescent Psychiatry; Erasmus University Medical Centre; Rotterdam Netherlands

2. Department of Radiology; Erasmus University Medical Centre; Rotterdam Netherlands

3. The Generation R Study Group, Erasmus University Medical Centre; Rotterdam Netherlands

4. The Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, NIH; Bethesda Maryland

5. Department of Pediatrics; Erasmus University Medical Centre; Rotterdam Netherlands

6. Department of Epidemiology; Erasmus University Medical Centre; Rotterdam Netherlands

7. Department of Biomedical Engineering and Clinical Imaging Research Center; National University of Singapore; Singapore Singapore

8. Singapore Institute for Clinical Sciences; Singapore Singapore

9. Autism and Developmental Medicine Institute, Geisinger Health System; Lewisburg Pennsylvania 17837

10. Department of Clinical Medicine at the Faculty of Health and Medical Sciences; University of Copenhagen; Copenhagen Denmark

Funder

Netherlands Organisation for Health Research and Development

EC Seventh Framework Programm

Stichting Sophia Kinderziekenhuis Fonds

Erasmus Medical Center

Erasmus University Rotterdam

Netherlands Organisation for Scientific Research

Ministry of Health and Welfare

Ministry of Youth and Families

Publisher

Wiley

Subject

Clinical Neurology,Neurology,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology,Anatomy

Reference38 articles.

1. Subtle in-scanner motion biases automated measurement of brain anatomy from in vivo MRI;Alexander-Bloch;Human Brain Mapping,2016

2. Automatic correction of motion artifacts in magnetic resonance images using an entropy focus criterion;Atkinson;IEEE Transactions on Medical Imaging,1997

3. Quality control of structural MRI images applied using FreeSurfer-A hands-on workflow to rate motion artifacts;Backhausen;Frontiers in Neuroscience,2016

4. Motion artifact control in body MR imaging;Barish;Magnetic Resonance Imaging Clinics of North America,1999

5. Motion artifact in magnetic resonance imaging: Implications for automated analysis;Blumenthal;NeuroImage,2002

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