Article

Hybrid deformable model for aneurysm segmentation

Authors:

Stefanie Demirci,

Guy Lejeune,

Nassir NavabAuthors Info & Claims

ISBI'09: Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro

Pages 33 - 36

Published: 28 June 2009 Publication History

Abstract

Automatic extraction of aortic aneurysm thrombus is a nontrivial challenge for existing segmentation algorithms. Due to similar intensity, the boundary to surrounding tissue is characterized by a small gradient. On the other hand, the aneurysm contains calcification spots that introduce wrong gradients. Therefore, purely intensity- or gradient-based methods fail to give optimal results. In this paper, we present a hybrid deformable model approach that integrates local and global image information and combines it with shape constraints. By the use of NURBS surfaces and distance functions, segmentation leakage into adjacent structures is prevented. The results of several experiments were evaluated by standard measures and expert inspection.

References

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Marko Subasic, Sven Loncaric, and Erich Sorantin, "3- d deformable model segmentation of abdominal aortic aneurysm," in Proc. SPIE Medical Imaging, 2001.

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Derek R. Magee, Andrew J. Bulpitt, and Berry Elizabeth, "Combining 3d deformable models and level set methods for the segmentation of abnormal aortic aneurysms," in Proc. BMVC, 2001.

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Feng Zhuge, Geoffrey D. Rubin, Shaohua Sun, and Sandy Napel, "An abdominal aortic aneurysm segmentation method: Level set with region and statistical information," Medical Physics, vol. 33, no. 5, pp. 1440-1453, 2006.

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Silvia D. Olabarriaga, Jean-Michel Rouet, Maxim Fradkin, Marcel Breeuwer, and Wiro J. Niessen, "Segmentation of thrombus in abdominal aortic aneurysms from cta with nonparametric statistical grey level appearance modeling," IEEE TMI, vol. 24, no. 4, pp. 477-485, 2005.

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Marleen de Bruijne, Bram van Ginneken, Max A. Viergever, and Wiro J. Niessen, "Adapting active shape models for 3d segmentation of tubular structures in medical images," in Proc. IPMI, 2003.

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Xiaolei Huang, Dimitris N. Metaxas, and Ting Chen, "Metamorphs: Deformable shape and texture models," in Proc. CVPR, 2004.

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Les Piegl and Wayne Tiller, The NURBS Book, Springer, 1997.

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Maiora JGraña M(2012)A hybrid segmentation of abdominal CT imagesProceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II10.1007/978-3-642-28931-6_40(416-423)Online publication date: 28-Mar-2012
https://dl.acm.org/doi/10.1007/978-3-642-28931-6_40
Freiman MEsses SJoskowicz LSosna J(2010)An iterative model-constrained graph-cut algorithm for abdominal aortic aneurysm thrombus segmentationProceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro10.5555/1855963.1856138(672-675)Online publication date: 14-Apr-2010
https://dl.acm.org/doi/10.5555/1855963.1856138

Hybrid deformable model for aneurysm segmentation
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems

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Published In

ISBI'09: Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro

June 2009

1405 pages

ISBN:9781424439317

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IEEE Press

Publication History

Published: 28 June 2009

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Maiora JGraña M(2012)A hybrid segmentation of abdominal CT imagesProceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II10.1007/978-3-642-28931-6_40(416-423)Online publication date: 28-Mar-2012
https://dl.acm.org/doi/10.1007/978-3-642-28931-6_40
Freiman MEsses SJoskowicz LSosna J(2010)An iterative model-constrained graph-cut algorithm for abdominal aortic aneurysm thrombus segmentationProceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro10.5555/1855963.1856138(672-675)Online publication date: 14-Apr-2010
https://dl.acm.org/doi/10.5555/1855963.1856138

Abstract

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Cited By

Recommendations

Model-based quantitative AAA image analysis using a priori knowledge

Automatic Segmentation of Abdominal Aortic Aneurysm Using Logical Algorithm

Automatic Abdominal Aortic Aneurysm segmentation in MR images

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