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Convolutional Neural Network-Based Regression for Quantification of Brain Characteristics Using MRI

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New Knowledge in Information Systems and Technologies (WorldCIST'19 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 931))

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Abstract

Preterm birth is connected to impairments and altered brain growth. Compared to their term born peers, preterm infants have a higher risk of behavioral and cognitive problems since most part of their brain development is in extra-uterine conditions. This paper presents different deep learning approaches with the objective of quantifying the volumes of 8 brain tissues and 5 other image-based descriptors that quantify the state of brain development. Two datasets were used: one with 86 MR brain images of patients around 30 weeks PMA and the other with 153 patients around 40 weeks PMA. Two approaches were evaluated: (1) using the full image as 3D input and (2) using multiple image slices as 3D input, both achieving promising results. A second study, using a dataset of MR brain images of rats, was also performed to assess the performance of this method with other brains. A 2D approach was used to estimate the volumes of 3 rat brain tissues.

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Acknowledgements

This work was supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013. We gratefully acknowledge the support of the NVIDIA Corporation with their donation of a Quadro P6000 board used in this research.

Author information

Authors and Affiliations

  1. Department of Informatics, School of Engineering, University of Minho, Braga, Portugal

    João Fernandes

  2. Algoritmi Centre, University of Minho, Braga, Portugal

    Victor Alves

  3. Images Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands

    Nadieh Khalili & Ivana Išgum

  4. Department of Neonatology, University Medical Center Utrecht, Utrecht, The Netherlands

    Manon J. N. L. Benders

  5. Eindhoven University of Technology, Eindhoven, The Netherlands

    Josien Pluim & Pim Moeskops

Authors
  1. João Fernandes
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  2. Victor Alves
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  3. Nadieh Khalili
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  4. Manon J. N. L. Benders
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  5. Ivana Išgum
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  6. Josien Pluim
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  7. Pim Moeskops
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Corresponding author

Correspondence to João Fernandes .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Universidade de Coimbra, Coimbra, Portugal

    Álvaro Rocha

  2. The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. Faculdade de Engenharia/LIACC, Universidade do Porto, Porto, Portugal

    Luís Paulo Reis

  4. DIMES, Università della Calabria, Arcavacata di Rende, Italy

    Sandra Costanzo

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Fernandes, J. et al. (2019). Convolutional Neural Network-Based Regression for Quantification of Brain Characteristics Using MRI. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) New Knowledge in Information Systems and Technologies. WorldCIST'19 2019. Advances in Intelligent Systems and Computing, vol 931. Springer, Cham. https://doi.org/10.1007/978-3-030-16184-2_55

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