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Authors: Alireza Fallahi 1 ; Mohammad Pooyan 1 ; Hassan Hashemi 2 ; Hassan Khotanlou 3 ; Mohammad Ali Oghabian 2 and Kavous Firuznia 2

Affiliations: 1 Shahed University, Iran, Islamic Republic of ; 2 Advanced Diagnostic and Interventional Radiology Research, Iran, Islamic Republic of ; 3 Bu-Ali Sina University, Iran, Islamic Republic of

ISBN: 978-989-674-027-6

Keyword(s): Uterine Fibroid, MRI Images, Image Segmentation, Chan-vese Level Set, Prior Shape Model.

Related Ontology Subjects/Areas/Topics: Applications ; Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Entertainment Imaging Applications ; Image and Video Coding and Compression ; Image Formation and Preprocessing ; Medical Imaging ; Pattern Recognition ; Software Engineering

Abstract: Uterine fibroid the most common benign tumor of the female pelvic affected 20%- 50% of the women in the world. The efficacy of medical treatment is gauged by shrinkage of the size of these tumors after surgery. Complex fibroids anatomy, nonhomogeneity region and missing boundary in some cases are a challenging task in the segmentation. In this paper, we present a method to robustly segment these fibroids on MRI and measure the volume. Our method is based on combination of two step Chan-Vese level set method and geometric shape prior model. With calculating an initial region inside the fibroid using Chan-Vese level sets method, rough segmentation obtained followed by a prior shape model. We found the algorithm efficient and that it has some good results.

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Paper citation in several formats:
Fallahi A.; Pooyan M.; Hashemi H.; Khotanlou H.; Ali Oghabian M.; Firuznia K. and (2010). UTERINE FIBROID SEGMENTATION ON MRI BASED ON CHAN-VESE LEVEL SET METHOD AND SHAPE PRIOR MODEL.In Proceedings of the International Conference on Imaging Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2010) ISBN 978-989-674-027-6, pages 51-55. DOI: 10.5220/0002831100510055

@conference{imagapp10,
author={Alireza Fallahi and Mohammad Pooyan and Hassan Hashemi and Hassan Khotanlou and Mohammad {Ali Oghabian} and Kavous Firuznia},
title={UTERINE FIBROID SEGMENTATION ON MRI BASED ON CHAN-VESE LEVEL SET METHOD AND SHAPE PRIOR MODEL},
booktitle={Proceedings of the International Conference on Imaging Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2010)},
year={2010},
pages={51-55},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002831100510055},
isbn={978-989-674-027-6},
}

TY - CONF

JO - Proceedings of the International Conference on Imaging Theory and Applications and International Conference on Information Visualization Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2010)
TI - UTERINE FIBROID SEGMENTATION ON MRI BASED ON CHAN-VESE LEVEL SET METHOD AND SHAPE PRIOR MODEL
SN - 978-989-674-027-6
AU - Fallahi, A.
AU - Pooyan, M.
AU - Hashemi, H.
AU - Khotanlou, H.
AU - Ali Oghabian, M.
AU - Firuznia, K.
PY - 2010
SP - 51
EP - 55
DO - 10.5220/0002831100510055

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