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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Detalles Bibliográficos
Autores principales: Bagci, Ulas, Yao, Jianhua, Miller-Jaster, Kirsten, Chen, Xinjian, Mollura, Daniel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3576352/
https://www.ncbi.nlm.nih.gov/pubmed/23431398
http://dx.doi.org/10.1371/journal.pone.0057105

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3576352/
https://www.ncbi.nlm.nih.gov/pubmed/23431398
http://dx.doi.org/10.1371/journal.pone.0057105

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