Statistical Models of Shape and Spatial Relation-application to Hippocampus Segmentation

Saïd Ettaïeb, Kamel Hamrouni, Su Ruan

Abstract

This paper presents a new method based both on Active Shape Model (ASM) and spatial distance model to segment brain structures. It combines two types of a priori knowledge: the structure shapes and the distances between them. This knowledge consists of shape and distance variability which are estimated during a training step. Then, the obtained models are used to guide simultaneously the evolution of initial structure shapes towards the target contours. The proposed models are applied to extract two hippocampal regions on coronal MRI of the brain. The obtained results are encouraging and show the performance of the proposed model.

References

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Paper Citation


in Harvard Style

Ettaïeb S., Hamrouni K. and Ruan S. (2014). Statistical Models of Shape and Spatial Relation-application to Hippocampus Segmentation . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 448-455. DOI: 10.5220/0004658404480455


in Bibtex Style

@conference{visapp14,
author={Saïd Ettaïeb and Kamel Hamrouni and Su Ruan},
title={Statistical Models of Shape and Spatial Relation-application to Hippocampus Segmentation},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={448-455},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004658404480455},
isbn={978-989-758-003-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - Statistical Models of Shape and Spatial Relation-application to Hippocampus Segmentation
SN - 978-989-758-003-1
AU - Ettaïeb S.
AU - Hamrouni K.
AU - Ruan S.
PY - 2014
SP - 448
EP - 455
DO - 10.5220/0004658404480455