
Proceedings Paper
DEeP random walksFormat | Member Price | Non-Member Price |
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Paper Abstract
In this paper, we proposed distance enforced penalized (DEeP) random walks segmentation framework to delineate
coupled boundaries by modifying classical random walks formulations. We take into account curves inter-dependencies
and incorporate associated distances into weight function of conventional random walker. This effectively leverages
segmentation of weaker boundaries guided by stronger counterparts, which is the main advantage over classical random
walks techniques where the weight function is only dependent on intensity differences between connected pixels,
resulting in unfavorable outcomes in the context of poor contrasted images. First, we applied our developed algorithm on
synthetic data and then on cardiac magnetic resonance (MR) images for detection of myocardium borders. We obtained
encouraging results and observed that proposed algorithm prevents epicardial border to leak into right ventricle or cross
back into endocardial border that often observe when conventional random walker is used. We applied our method on
forty cardiac MR images and quantified the results with corresponding manual traced borders as ground truths. We
found the Dice coefficients 70%± 14% and 43% ±14% respectively for DEeP random walks and conventional one.
Paper Details
Date Published: 13 March 2013
PDF: 6 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86693O (13 March 2013); doi: 10.1117/12.2006902
Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)
PDF: 6 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86693O (13 March 2013); doi: 10.1117/12.2006902
Show Author Affiliations
Mandana Javanshir Moghaddam, Royal Institute of Technology KTH (Sweden)
Abouzar Eslami, Technical Univ. of Munich (Germany)
Abouzar Eslami, Technical Univ. of Munich (Germany)
Nassir Navab, Technical Univ. of Munich (Germany)
Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)
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