A probabilistic level set formulation for interactive organ segmentation

Daniel Cremers; Oliver Fluck; Mikael Rousson; Shmuel Aharon

doi:10.1117/12.708609

3 March 2007 A probabilistic level set formulation for interactive organ segmentation

Daniel Cremers, Oliver Fluck, Mikael Rousson, Shmuel Aharon

Proceedings Volume 6512, Medical Imaging 2007: Image Processing; 65120V (2007) https://doi.org/10.1117/12.708609
Event: Medical Imaging, 2007, San Diego, CA, United States

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.

Citation Download Citation

Daniel Cremers, Oliver Fluck, Mikael Rousson, and Shmuel Aharon "A probabilistic level set formulation for interactive organ segmentation", Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 65120V (3 March 2007); https://doi.org/10.1117/12.708609

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available