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Authors: Christian Neumann 1 ; Klaus-Dietz Tönnies 2 and Regina Pohle-Fröhlich 1

Affiliations: 1 Hochschule Niederrhein University of Applied Sciences, Germany ; 2 Otto-von-Guericke University of Magdeburg, Germany

ISBN: 978-989-758-290-5

Keyword(s): CNN, Cerebral, DSA Series, Vessel Segmentation.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Medical Image Applications ; Segmentation and Grouping

Abstract: The U-net is a promising architecture for medical segmentation problems. In this paper, we show how this architecture can be effectively applied to cerebral DSA series. The usage of multiple images as input allows for better distinguishing between vessel and background. Furthermore, the U-net can be trained with a small corpus when combined with useful data augmentations like mirroring, rotation, and additionally biasing. Our variant of the network achieves a DSC of 87.98% on the segmentation task. We compare this to different configurations and discuss the effect on various artifacts like bones, glue, and screws.

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Paper citation in several formats:
Neumann, C.; Tönnies, K. and Pohle-Fröhlich, R. (2018). AngioUnet - A Convolutional Neural Network for Vessel Segmentation in Cerebral DSA Series.In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-290-5, pages 331-338. DOI: 10.5220/0006570603310338

@conference{visapp18,
author={Christian Neumann. and Klaus{-}Dietz Tönnies. and Regina Pohle{-}Fröhlich.},
title={AngioUnet - A Convolutional Neural Network for Vessel Segmentation in Cerebral DSA Series},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,},
year={2018},
pages={331-338},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006570603310338},
isbn={978-989-758-290-5},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,
TI - AngioUnet - A Convolutional Neural Network for Vessel Segmentation in Cerebral DSA Series
SN - 978-989-758-290-5
AU - Neumann, C.
AU - Tönnies, K.
AU - Pohle-Fröhlich, R.
PY - 2018
SP - 331
EP - 338
DO - 10.5220/0006570603310338

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