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Authors: Gaetan Galisot 1 ; Thierry Brouard 1 ; Jean-Yves Ramel 1 and Elodie Chaillou 2

Affiliations: 1 LIFAT Tours, Université de Tours, 64 avenue Jean Portalis, 37000, Tours and France ; 2 PRC, INRA, CNRS, IFCE, Université de Tours, 37380, Nouzilly and France

ISBN: 978-989-758-354-4

Keyword(s): 3D Image Segmentation, Local Atlas, Voxels Classification.

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: Automatic or interactive segmentation tools for 3D medical images have been developed to help the clinicians. Atlas-based methods are one of the most usual techniques to localized anatomical structures. They have shown to be efficient with various types of medical images and various types of organs. However, a registration step is needed to perform an atlas-based segmentation which can be very time consuming. Local atlases coupled with spatial relationships have been proposed to solve this issue. Local atlases are defined on a sub-part of the image enabling a fast registration step. The positioning of these local atlases on the whole image can be done automatically with learned spatial relationships or interactively by a user when the automatic positioning is not well performed. In this article, different classification methods possibly included in local atlases segmentation methods are compared. Human brain and sheep brain MRI images have been used as databases for the experiments. D epending on the choice of the method, segmentation quality and computation time are very different. Graph-cut or CNN segmentation methods have shown to be more suitable for interactive segmentation because of their low computation time. Multi-atlas based methods like local weighted majority voting are more suitable for automatic process. (More)

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Paper citation in several formats:
Galisot, G.; Brouard, T.; Ramel, J. and Chaillou, E. (2019). A Comparative Study on Voxel Classification Methods for Atlas based Segmentation of Brain Structures from 3D MRI Images.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, ISBN 978-989-758-354-4, pages 341-350. DOI: 10.5220/0007358503410350

@conference{visapp19,
author={Gaetan Galisot. and Thierry Brouard. and Jean{-}Yves Ramel. and Elodie Chaillou.},
title={A Comparative Study on Voxel Classification Methods for Atlas based Segmentation of Brain Structures from 3D MRI Images},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP,},
year={2019},
pages={341-350},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007358503410350},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP,
TI - A Comparative Study on Voxel Classification Methods for Atlas based Segmentation of Brain Structures from 3D MRI Images
SN - 978-989-758-354-4
AU - Galisot, G.
AU - Brouard, T.
AU - Ramel, J.
AU - Chaillou, E.
PY - 2019
SP - 341
EP - 350
DO - 10.5220/0007358503410350

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