Ensemble of 3D CNN Regressors with Data Fusion for Fluid Intelligence Prediction

Marina Pominova, Anna Kuzina, Ekaterina Kondrateva, Svetlana Sushchinskaya, Evgeny Burnaev, Vyacheslav Yarkin, Maxim Sharaev

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    2 Citations (Scopus)

    Abstract

    In this work, we aimed at predicting children’s fluid intelligence scores based on structural T1-weighted MR images from the largest long-term study of brain development and child health. The target variable was regressed on a data collection site, sociodemographic variables, and brain volume, thus being independent to the potentially informative factors, which were not directly related to the brain functioning. We investigated both feature extraction and deep learning approaches as well as different deep CNN architectures and their ensembles. We proposed an advanced architecture of VoxCNNs ensemble, which yields MSE (92.838) on a blind test.

    Original languageEnglish
    Title of host publicationAdolescent Brain Cognitive Development Neurocognitive Prediction - 1st Challenge, ABCD-NP 2019, held in Conjunction with MICCAI 2019, Proceedings
    EditorsKilian M. Pohl, Ehsan Adeli, Wesley K. Thompson, Marius George Linguraru
    PublisherSpringer
    Pages158-166
    Number of pages9
    ISBN (Print)9783030319007
    DOIs
    Publication statusPublished - 2019
    Event1st Challenge in Adolescent Brain Cognitive Development Neurocognitive Prediction, ABCD-NP 2019, held in conjunction with the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2019 - Shenzhen, China
    Duration: 13 Oct 201913 Oct 2019

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11791 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference1st Challenge in Adolescent Brain Cognitive Development Neurocognitive Prediction, ABCD-NP 2019, held in conjunction with the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2019
    Country/TerritoryChina
    CityShenzhen
    Period13/10/1913/10/19

    Keywords

    • 3D convolutional neural networks
    • Deep learning
    • Fluid intelligence prediction
    • MRI analysis
    • VoxCNN ensemble

    Fingerprint

    Dive into the research topics of 'Ensemble of 3D CNN Regressors with Data Fusion for Fluid Intelligence Prediction'. Together they form a unique fingerprint.

    Cite this