Scientific article
OA Policy
English

Novel multimodality segmentation using level sets and Jensen-Rényi divergence

Published inMedical physics, vol. 40, no. 12, 121908
Publication date2013
Abstract

Positron emission tomography (PET) is playing an increasing role in radiotherapy treatment planning. However, despite progress, robust algorithms for PET and multimodal image segmentation are still lacking, especially if the algorithm were extended to image-guided and adaptive radiotherapy (IGART). This work presents a novel multimodality segmentation algorithm using the Jensen-Rényi divergence (JRD) to evolve the geometric level set contour. The algorithm offers improved noise tolerance which is particularly applicable to segmentation of regions found in PET and cone-beam computed tomography.

Citation (ISO format)
MARKEL, Daniel, ZAIDI, Habib, EL NAQA, Issam. Novel multimodality segmentation using level sets and Jensen-Rényi divergence. In: Medical physics, 2013, vol. 40, n° 12, p. 121908. doi: 10.1118/1.4828836
Main files (1)
Article (Published version)
accessLevelPublic
Identifiers
Journal ISSN0094-2405
538views
514downloads

Technical informations

Creation08/06/2014 1:14:00 PM
First validation08/06/2014 1:14:00 PM
Update time01/20/2025 9:41:31 AM
Status update01/20/2025 9:41:31 AM
Last indexation01/20/2025 9:58:47 AM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack