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Image Retrieval for Alzheimer’s Disease Based on Brain Atrophy Pattern

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ICT Innovations 2017 (ICT Innovations 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 778))

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Abstract

The aim of the paper is to present image retrieval for Alzheimer’s Disease (AD) based on brain atrophy pattern captured by the SPARE-AD (Spatial Pattern of Abnormality for Recognition of Early Alzheimer’s Disease) index. SPARE-AD provides individualized scores of diagnostic and predictive value found to be far beyond standard structural measures. The index was incorporated in the image signature as a representation of the brain atrophy. To evaluate its influence to the retrieval results, Magnetic Resonance Images (MRI) provided by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were used. For this research, baseline images of the patients with diagnosed AD and normal controls (NL) were selected from the dataset, including 416 subjects in total. The obtained experimental results showed that the approach used in this research provides improved retrieval performance, by using semantically precise and powerful, yet low dimensional image descriptor.

*Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf; e-mail: edrake@bwh.harvard.edu.

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Acknowledgement

Data collection and sharing for this study 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). 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.; Bio-gen; 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.

Authors also acknowledge the support of the European Commission through the project MAESTRA - Learning from Massive, Incompletely annotated, and Structured Data (Grant number ICT-2013-612944).

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Authors and Affiliations

  1. Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Rugjer Boshkovik 16, PO Box 393, Skopje, Macedonia

    Katarina Trojacanec, Slobodan Kalajdziski, Ivan Kitanovski, Ivica Dimitrovski & Suzana Loshkovska

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  1. Katarina Trojacanec
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  2. Slobodan Kalajdziski
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  3. Ivan Kitanovski
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for the Alzheimer’s Disease Neuroimaging Initiative*

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Correspondence to Katarina Trojacanec .

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Editors and Affiliations

  1. Computer Science and Engineering, Ss. Cyril and Methodius University, Skopje, Macedonia

    Dimitar Trajanov

  2. Computer Science and Engineering, Ss. Cyril and Methodius University , Skopje, Macedonia

    Verica Bakeva

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Trojacanec, K., Kalajdziski, S., Kitanovski, I., Dimitrovski, I., Loshkovska, S., for the Alzheimer’s Disease Neuroimaging Initiative*. (2017). Image Retrieval for Alzheimer’s Disease Based on Brain Atrophy Pattern. In: Trajanov, D., Bakeva, V. (eds) ICT Innovations 2017. ICT Innovations 2017. Communications in Computer and Information Science, vol 778. Springer, Cham. https://doi.org/10.1007/978-3-319-67597-8_16

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  • DOI: https://doi.org/10.1007/978-3-319-67597-8_16

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