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WorldCIST'19 - 7th World Conference on Information Systems and Technologies

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Convolutional Neural Network-based regression for quantification of brain characteristics using MRI

Preterm birth is connected to impairments and altered brain growth. Compared to their term born peers, preterm infants have a higher risk of behav-ioral and cognitive problems since most part of their brain development is in ex-tra-uterine conditions. This paper presents different deep learning approaches with the objective of quantifying the volumes of 8 brain tissues and 5 other im-age-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 eval-uated: 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.

João Fernandes
University of Minho
Portugal

Victor Alves
University of Minho
Portugal

Nadieh Khalili
University Medical Center Utrecht
Netherlands

Manon Benders
University Medical Center Utrecht
Netherlands

Ivana Išgum
University Medical Center Utrecht
Netherlands

Josien Pluim
Eindhoven University of Technology
Netherlands

Pim Moeskops
Eindhoven University of Technology
Netherlands

 


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