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Analysis of institutional authors

Ninerola-Baizan, AidaAuthorSala-Llonch, RoserAuthor

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March 8, 2025
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JUMP: A JOINT MULTIMODAL REGISTRATION PIPELINE FOR NEUROIMAGING WITH MINIMAL PREPROCESSING

Publicated to: Proceedings (International Symposium On Biomedical Imaging). - 2024-01-01 (), DOI: 10.1109/ISBI56570.2024.10635235

Authors:

Casamitjana, A; Iglesias, JE; Tudela, R; Niñerola-Baizán, A; Sala-Llonch, R
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Affiliations

Harvard Med Sch, Boston, MA USA - Author
Hosp Clin Barcelona, Dept Nucl Med, Barcelona, Spain - Author
Inst Invest Biomed August Pi & Sunyer IDIBAPS, Barcelona, Spain - Author
ISCIII, Ctr Invest Biomed Red Bioingn Biomat & Nanomed, Madrid, Spain - Author
MGH, Martinos Ctr Biomed Imaging, Boston, MA USA - Author
MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA USA - Author
UCL, Ctr Med Image Comp, London, England - Author
Univ Barcelona, Dept Biomed, Inst Neurociencies, Barcelona, Spain - Author
Univ Politecn Cataluna, Barcelona, Spain - Author
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Abstract

We present a pipeline for unbiased and robust multimodal registration of neuroimaging modalities with minimal preprocessing. While typical multimodal studies need to use multiple independent processing pipelines, with diverse options and hyperparameters, we propose a single and structured framework to jointly process different image modalities. The use of state-of-the-art learning-based techniques enables fast inferences, which makes the presented method suitable for large-scale and/or multi-cohort datasets with a diverse number of modalities per session. The pipeline currently works with structural MRI, resting state fMRI and amyloid PET images. We show the predictive power of the derived biomarkers using in a case-control study and study the cross-modal relationship between different image modalities. The code can be found in https://github.com/acasamitjana/JUMP.
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Keywords

Alzheimer's diseasAlzheimer's diseaseAlzheimers diseaseAmyloid petConnectivityHyper-parameterImage codingImage modalityImage registrationMulti-modalMultimodal registrationNetworNeurodegenerative diseasesNeuroimagingPipeline codesPre-processingResting stateResting-state fmriState of the art

Quality index

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 2026-02-01:

  • 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: 2 (PlumX).
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: United Kingdom; United States of America.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: Last Author (Sala Llonch, Roser).

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Awards linked to the item

Adria Casamitjana received funding from Ministry of Universities and Recovery, Transformation and Resilience Plan, through UPC (Grant No 2021UPC-MS-67573). R.S has received financial support from the Generalitat de Catalunya (2021-SGR00523), the Maria de Maeztu Unit of Excellence (Institute of Neurosciences, University of Barcelona, CEX2021-001159-M), and the Spanish Ministry of Science and Innovation (PID2020-118386RA-I00/AEI/10.13039/501100011033)
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