@inproceedings{23c1125b8c55441aaad41c25ad929cb6,
title = "A probabilistic level set formulation for interactive organ segmentation",
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.",
keywords = "CT, Graphics processor unit (GPU), Interactive, Level set, MR, Medical imaging, Probabilistic, Segmentation, Ultrasound, User interaction",
author = "Daniel Cremers and Oliver Fluck and Mikael Rousson and Shmuel Aharon",
note = "Funding Information: This work was supported by the Chinese National High Technology Project and Nature Science Foundation of China. ; Medical Imaging 2007: Image Processing ; Conference date: 18-02-2007 Through 20-02-2007",
year = "2007",
doi = "10.1117/12.708609",
language = "English",
isbn = "0819466301",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
number = "PART 1",
booktitle = "Medical Imaging 2007",
edition = "PART 1",
}