Single-Input Multi-Output U-Net for Automated 2D Foetal Brain Segmentation of MR Images

Single-Input Multi-Output U-Net for Automated 2D Foetal Brain Segmentation of MR Images

In this work, we develop the Single-Input Multi-Output U-Net (SIMOU-Net), a hybrid network for foetal brain segmentation inspired by the original U-Net fused with the holistically nested edge detection (HED) network. The SIMOU-Net is similar to the original U-Net but it has a deeper architecture and...

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Bibliographic Details
Main Authors: Andrik Rampun, Deborah Jarvis, Paul D. Griffiths, Reyer Zwiggelaar, Bryan W. Scotney, Paul A. Armitage
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Journal of Imaging
Subjects:
foetal brain segmentation
MRI
U-Net
HED network
deep learning
convolutional neural network
Online Access:https://www.mdpi.com/2313-433X/7/10/200

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