Fast MRI whole brain segmentation with fully convolutional neural networks

Abhijit Guha Roy; Sailesh Conjeti; Nassir Navab; Christian Wachinger

doi:10.1007/978-3-662-56537-7_26

Fast MRI whole brain segmentation with fully convolutional neural networks

Abhijit Guha Roy, Sailesh Conjeti, Nassir Navab, Christian Wachinger

Informatics 16 - Chair of Computer Aided Medical Procedures

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Whole brain segmentation from structural MRI-T1 scan is a prerequisite for most morphological analyses, but requires hours of processing time and therefore delays the availability of image markers after scan acquisition. We introduced a fully convolution neural network (F-CNN) that segments a brain scan in several seconds [1]. Training deep F-CNNs for semantic image segmentation requires access to abundant labeled data.

Original language	English
Title of host publication	Informatik aktuell
Editors	Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus H. Maier-Hein, Christoph Palm, Thomas Tolxdorff
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	42
Number of pages	1
ISBN (Print)	9783540295945, 9783540748366, 9783540853237, 9783642246579, 9783642337062, 9783642413087, 9783662451083, 9783662557846, 9783662565360, 9783662580950
DOIs	https://doi.org/10.1007/978-3-662-56537-7_26
State	Published - 2018
Event	Workshop on Bildverarbeitung fur die Medizin, 2018 - Erlangen, Germany Duration: 11 Mar 2018 → 13 Mar 2018

Publication series

Name	Informatik aktuell
Volume	0
ISSN (Print)	1431-472X

Conference

Conference	Workshop on Bildverarbeitung fur die Medizin, 2018
Country/Territory	Germany
City	Erlangen
Period	11/03/18 → 13/03/18

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10.1007/978-3-662-56537-7_26

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Roy, A. G., Conjeti, S., Navab, N., & Wachinger, C. (2018). Fast MRI whole brain segmentation with fully convolutional neural networks. In A. Maier, T. M. Deserno, H. Handels, K. H. Maier-Hein, C. Palm, & T. Tolxdorff (Eds.), Informatik aktuell (pp. 42). (Informatik aktuell; Vol. 0). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-662-56537-7_26

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title = "Fast MRI whole brain segmentation with fully convolutional neural networks",

abstract = "Whole brain segmentation from structural MRI-T1 scan is a prerequisite for most morphological analyses, but requires hours of processing time and therefore delays the availability of image markers after scan acquisition. We introduced a fully convolution neural network (F-CNN) that segments a brain scan in several seconds [1]. Training deep F-CNNs for semantic image segmentation requires access to abundant labeled data.",

author = "Roy, {Abhijit Guha} and Sailesh Conjeti and Nassir Navab and Christian Wachinger",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag GmbH Deutschland 2018.; Workshop on Bildverarbeitung fur die Medizin, 2018 ; Conference date: 11-03-2018 Through 13-03-2018",

year = "2018",

doi = "10.1007/978-3-662-56537-7_26",

language = "English",

isbn = "9783540295945",

series = "Informatik aktuell",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "42",

editor = "Andreas Maier and Deserno, {Thomas M.} and Heinz Handels and Maier-Hein, {Klaus H.} and Christoph Palm and Thomas Tolxdorff",

booktitle = "Informatik aktuell",

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Roy, AG, Conjeti, S, Navab, N & Wachinger, C 2018, Fast MRI whole brain segmentation with fully convolutional neural networks. in A Maier, TM Deserno, H Handels, KH Maier-Hein, C Palm & T Tolxdorff (eds), Informatik aktuell. Informatik aktuell, vol. 0, Springer Science and Business Media Deutschland GmbH, pp. 42, Workshop on Bildverarbeitung fur die Medizin, 2018, Erlangen, Germany, 11/03/18. https://doi.org/10.1007/978-3-662-56537-7_26

Fast MRI whole brain segmentation with fully convolutional neural networks. / Roy, Abhijit Guha; Conjeti, Sailesh; Navab, Nassir et al.
Informatik aktuell. ed. / Andreas Maier; Thomas M. Deserno; Heinz Handels; Klaus H. Maier-Hein; Christoph Palm; Thomas Tolxdorff. Springer Science and Business Media Deutschland GmbH, 2018. p. 42 (Informatik aktuell; Vol. 0).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N1 - Publisher Copyright: © Springer-Verlag GmbH Deutschland 2018.

PY - 2018

Y1 - 2018

N2 - Whole brain segmentation from structural MRI-T1 scan is a prerequisite for most morphological analyses, but requires hours of processing time and therefore delays the availability of image markers after scan acquisition. We introduced a fully convolution neural network (F-CNN) that segments a brain scan in several seconds [1]. Training deep F-CNNs for semantic image segmentation requires access to abundant labeled data.

AB - Whole brain segmentation from structural MRI-T1 scan is a prerequisite for most morphological analyses, but requires hours of processing time and therefore delays the availability of image markers after scan acquisition. We introduced a fully convolution neural network (F-CNN) that segments a brain scan in several seconds [1]. Training deep F-CNNs for semantic image segmentation requires access to abundant labeled data.

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A2 - Maier-Hein, Klaus H.

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T2 - Workshop on Bildverarbeitung fur die Medizin, 2018

Y2 - 11 March 2018 through 13 March 2018

ER -

Fast MRI whole brain segmentation with fully convolutional neural networks

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