Isointense infant brain MRI segmentation with a dilated convolutional neural network

P. Moeskops; J.P.W. Pluim

Isointense infant brain MRI segmentation with a dilated convolutional neural network

P. Moeskops
, J.P.W. Pluim

Medical Image Analysis

Onderzoeksoutput: Bijdrage aan congres › Paper › Academic

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Samenvatting

Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter. In this study, we use a dilated triplanar convolutional neural network in combination with a non-dilated 3D convolutional neural network for the segmentation of white matter, gray matter and cerebrospinal fluid in infant brain MR images, as provided by the MICCAI grand challenge on 6-month infant brain MRI segmentation.

Originele taal-2	Engels
Status	Gepubliceerd - 9 aug. 2017
Evenement	MICCAI grand challenge on 6-month infant brain MRI segmentation - Quebec City, Canada Duur: 14 sep. 2017 → 14 sep. 2017 http://iseg2017.web.unc.edu/

Congres

Congres	MICCAI grand challenge on 6-month infant brain MRI segmentation
Land/Regio	Canada
Stad	Quebec City
Periode	14/09/17 → 14/09/17
Internet adres	http://iseg2017.web.unc.edu/

Bibliografische nota

MICCAI grand challenge on 6-month infant brain MRI segmentation

Trefwoorden

cs.CV

Toegang tot document

arXiv versionIngediend manuscript, 225 KB

https://arxiv.org/pdf/1708.02757.pdf

Citeer dit

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