SEGMENTATION OF VESSEL GEOMETRIES FROM MEDICAL IMAGES USING GPF DEFORMABLE MODEL

Si Yong Yeo, Igor Sazanov, Perumal Nithiarasu, Xianghua Xie

Abstract

We present a method for the reconstruction of vascular geometries from medical images. Image denoising is performed using vessel enhancing diffusion, which can smooth out image noise and enhance vessel structures. The Canny edge detection technique which produces object edges with single pixel width is used for accurate detection of the lumen boundaries. The image gradients are then used to compute the geometric potential field which gives a global representation of the geometric configuration. The deformable model uses a regional constraint to suppress calcified regions for accurate segmentation of the vessel geometries. The proposed framework show high accuracy when applied to the segmentation of the carotid arteries from CT images.

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Paper Citation


in Harvard Style

Yeo S., Xie X., Nithiarasu P. and Sazanov I. (2012). SEGMENTATION OF VESSEL GEOMETRIES FROM MEDICAL IMAGES USING GPF DEFORMABLE MODEL . In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: SADM, (ICPRAM 2012) ISBN 978-989-8425-98-0, pages 323-332. DOI: 10.5220/0003849303230332


in Bibtex Style

@conference{sadm12,
author={Si Yong Yeo and Xianghua Xie and Perumal Nithiarasu and Igor Sazanov},
title={SEGMENTATION OF VESSEL GEOMETRIES FROM MEDICAL IMAGES USING GPF DEFORMABLE MODEL},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: SADM, (ICPRAM 2012)},
year={2012},
pages={323-332},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003849303230332},
isbn={978-989-8425-98-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: SADM, (ICPRAM 2012)
TI - SEGMENTATION OF VESSEL GEOMETRIES FROM MEDICAL IMAGES USING GPF DEFORMABLE MODEL
SN - 978-989-8425-98-0
AU - Yeo S.
AU - Xie X.
AU - Nithiarasu P.
AU - Sazanov I.
PY - 2012
SP - 323
EP - 332
DO - 10.5220/0003849303230332