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Analysis of institutional authors

Platero Gaona, Carlos AntonioAuthorPlatero, CarlosAuthorCarmen Tobar, M.Author

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June 9, 2019
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Combining a Patch-based Approach with a Non-rigid Registration-based Label Fusion Method for the Hippocampal Segmentation in Alzheimer's Disease

Publicated to: NEUROINFORMATICS. 15 (2): 165-183 - 2017-04-01 15(2), DOI: 10.1007/s12021-017-9323-3

Authors:

Platero, Carlos; Carmen Tobar, M
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Affiliations

Tech Univ Madrid, Hlth Sci Technol Grp, Ronda Valencia 3, Madrid 28012, Spain - Author

Abstract

We provide and evaluate an open-source software solution for automatically hippocampal segmentation from T1-weighted (T1w) magnetic resonance imaging (MRI). The method is applied for measuring the hippocampal volume, which allows discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and elderly controls (NC). The method is based on a fast patch-based label fusion method, whose selected patches and their weights are calculated from a combination of similarity measures between patches using intensity-based distances and labeling-based distances. These combined similarity measures produces better selection of the patches, and their weights are more robust. The algorithm is trained with the Harmonized Hippocampal Protocol (HarP). The proposal is compared with FreeSurfer and other label fusion methods. To evaluate the performance and the robustness of the proposed label fusion method, we employ two databases of T1w MRI of human brains. For AD vs NC, we obtain a high degree of accuracy, approximately 90 %. For MCI vs NC, we obtain accuracies around 75 %. The average time for the hippocampal segmentation from a T1w MRI is less than 17 minutes.
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Keywords

atlas-based segmentationhippocampal segmentationimage registrationmagnetic resonance imagingAdni harmonized protocolAgedAged, 80 and overAlzheimer diseaseAnalysis of varianceAtlas-based segmentationAutomatic segmentationBrain extractionCognitive dysfunctionDatabases, factualFemaleHippocampal segmentationHippocampusHumansImage processing, computer-assistedImage registrationMagnetic resonance imagingMagnetic-resonance imagesMaleMental status scheduleMild cognitive impairmentMr-imagesMulti-atlas segmentationMutual informationOptimizationPatch-based label fusionPattern recognition, automatedValidation

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal NEUROINFORMATICS due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2017, it was in position 13/105, thus managing to position itself as a Q1 (Primer Cuartil), in the category Computer Science, Interdisciplinary Applications.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-27:

  • WoS: 14
  • Scopus: 17
  • Europe PMC: 7
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-27:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 33.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 33 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 10.
  • The number of mentions on the social network X (formerly Twitter): 1 (Altmetric).
  • The number of mentions in news outlets: 1 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/92041/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 31
  • Downloads: 23
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (PLATERO DUEÑAS, CARLOS) and Last Author (TOBAR PUENTE, M. DEL CARMEN).

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Awards linked to the item

Data collection for this study was funded by the ADNI (National Institutes of Health Grant U01 AG024904) and the Laboratory of Cognitive and Computational Neuroscience (LCCN) of the Center of Biomedical Technology (Technical University of Madrid). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering and and through generous contributions from the following: Alzheimer's Association; Alzheimer's Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company.
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