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Introducing a gatekeeping system for amyloid status assessment in mild cognitive impairment.

Autor: Doering E; German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany. elena.doering@uk-koeln.de.; University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany. elena.doering@uk-koeln.de., Hoenig MC; German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.; Institute for Neuroscience and Medicine II-Molecular Organization of the Brain, Research Center Juelich, Jülich, Germany., Bischof GN; German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.; Institute for Neuroscience and Medicine II-Molecular Organization of the Brain, Research Center Juelich, Jülich, Germany., Bohn KP; Klinikum Dritter Orden, Department of Radiology and Nuclear Medicine, Munich, Germany., Ellingsen LM; Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.; Department of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland., van Eimeren T; German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.; University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany., Drzezga A; German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.; University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany.; Institute for Neuroscience and Medicine II-Molecular Organization of the Brain, Research Center Juelich, Jülich, Germany.

Publikováno v: European journal of nuclear medicine and molecular imaging [Eur J Nucl Med Mol Imaging] 2022 Nov; Vol. 49 (13), pp. 4478-4489. Date of Electronic Publication: 2022 Jul 14.

Applications of a deep learning method for anti-aliasing and super-resolution in MRI.

Autor: Zhao C; Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA. Electronic address: czhao20@jhu.edu., Shao M; Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA., Carass A; Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA., Li H; Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA., Dewey BE; Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA; Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA., Ellingsen LM; Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA; Department of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland., Woo J; Department of Radiology, Harvard Medical School, Boston, MA, USA; Massachusetts General Hospital, Boston, MA, USA., Guttman MA; Johns Hopkins University School of Medicine, Baltimore, MD, USA., Blitz AM; Johns Hopkins University School of Medicine, Baltimore, MD, USA., Stone M; Department of Neural and Pain Sciences, University of Maryland, Baltimore, MD, USA., Calabresi PA; Johns Hopkins University School of Medicine, Baltimore, MD, USA., Halperin H; Johns Hopkins University School of Medicine, Baltimore, MD, USA., Prince JL; Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA; Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Publikováno v: Magnetic resonance imaging [Magn Reson Imaging] 2019 Dec; Vol. 64, pp. 132-141. Date of Electronic Publication: 2019 Jun 24.

SegAE: Unsupervised white matter lesion segmentation from brain MRIs using a CNN autoencoder.

Autor: Atlason HE; Department of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland., Love A; Department of Medicine, University of Iceland, Reykjavik, Iceland; Department of Radiology, Landspitali - University Hospital, Reykjavik, Iceland., Sigurdsson S; The Icelandic Heart Association, Kopavogur, Iceland., Gudnason V; Department of Medicine, University of Iceland, Reykjavik, Iceland; The Icelandic Heart Association, Kopavogur, Iceland., Ellingsen LM; Department of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA. Electronic address: lotta@hi.is.

Publikováno v: NeuroImage. Clinical [Neuroimage Clin] 2019; Vol. 24, pp. 102085. Date of Electronic Publication: 2019 Nov 09.

Shortcomings of Ventricle Segmentation Using Deep Convolutional Networks.

Autor: Shao M; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA., Han S; Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.; Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD 20892, USA., Carass A; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA.; Department of Computer Science, The Johns Hopkins University, Baltimore, MD 21218, USA., Li X; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA., Blitz AM; Department of Radiology and Radiological Science, The Johns Hopkins University, Baltimore, MD 21287, USA., Prince JL; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA.; Department of Computer Science, The Johns Hopkins University, Baltimore, MD 21218, USA., Ellingsen LM; Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA.; Department of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland.

Publikováno v: Understanding and interpreting machine learning in medical image computing applications : first international workshops, MLCN 2018, DLF 2018, and iMIMIC 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 16-20, 2018 :.. [Underst Interpret Mach Learn Med Image Comput Appl (2018)] 2018 Sep; Vol. 11038, pp. 79-86. Date of Electronic Publication: 2018 Oct 24.