Title
Automatic lung tumor segmentation on PET images based on random walks and tumor growth model
Abstract
The segmentation of tumor on PET images is an important step for treatment planning process during the radiotherapy. In this paper, we present an automatic segmentation method on PET images based on the random walks (RW) algorithm. We propose an extension of the random walks framework to integrate a tumor evolution information, which is the predicted tumor region resulting from a model for lung tumor growth and response to radiotherapy. The region of interest (ROI) and labeled seeds are automatically generated. Our approach is compared to the well-known 40% thresholding method, an adaptive thresholding method, a statistical method (FLAB), and a traditional RW algorithm. The good performance of our method has been confirmed on 7 lung tumor patients who are treated with radiotherapy.
Year
DOI
Venue
2014
10.1109/ISBI.2014.6868136
ISBI
Keywords
DocType
ISSN
labeled seeds,radiation therapy,random walks,radiotherapy,random processes,automatic lung tumor segmentation,random walk algorithm,image segmentation,lung tumor growth model,lung,PET,PET images,treatment planning process,lung tumor patients,positron emission tomography,tumours,Tumor segmentation,tumor growth model,medical image processing
Conference
1945-7928
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Hongmei Mi1121.61
Caroline Petitjean239028.57
Bernard Dubray3122.62
Pierre Vera440.77
Ruan Su555953.00