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Proceedings Paper

A probabilistic level set formulation for interactive organ segmentation
Author(s): Daniel Cremers; Oliver Fluck; Mikael Rousson; Shmuel Aharon
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Paper Abstract

Level set methods have become increasingly popular as a framework for image segmentation. Yet when used as a generic segmentation tool, they suffer from an important drawback: Current formulations do not allow much user interaction. Upon initialization, boundaries propagate to the final segmentation without the user being able to guide or correct the segmentation. In the present work, we address this limitation by proposing a probabilistic framework for image segmentation which integrates input intensity information and user interaction on equal footings. The resulting algorithm determines the most likely segmentation given the input image and the user input. In order to allow a user interaction in real-time during the segmentation, the algorithm is implemented on a graphics card and in a narrow band formulation.

Paper Details

Date Published: 3 March 2007
PDF: 9 pages
Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 65120V (3 March 2007); doi: 10.1117/12.708609
Show Author Affiliations
Daniel Cremers, Univ. of Bonn (Germany)
Oliver Fluck, Siemens Corporate Research (United States)
Mikael Rousson, Siemens Corporate Research (United States)
Shmuel Aharon, Siemens Corporate Research (United States)

Published in SPIE Proceedings Vol. 6512:
Medical Imaging 2007: Image Processing
Josien P. W. Pluim; Joseph M. Reinhardt, Editor(s)

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