Predicting future morphological changes of lesions from radiotracer uptake in 18F-FDG-PET images.

Predicting future morphological changes of lesions from radiotracer uptake in 18F-FDG-PET images.

We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on (18)F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented...

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Bibliographic Details
Main Authors: Ulas Bagci, Jianhua Yao, Kirsten Miller-Jaster, Xinjian Chen, Daniel J Mollura
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0057105&type=printable
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