Automatic tumour delineation in whole body PET/CT images Journal Article


Authors: Huang, X.; Zhu, Y.; Li, H.; Guan, H.; Potesil, V.; Song, Y.; Kubota, T.; Zhou, X. S.
Article Title: Automatic tumour delineation in whole body PET/CT images
Abstract: We propose a new method for automated delineation of tumour boundaries by using joint information from whole-body PET and diagnostic CT images. Due to varying levels of FDG uptake in different organs, we apply locally adaptive thresholds of SUV to acquire an initial estimate of hot spot locations and shape in PET images. The hot spot boundaries are further improved by applying Competition Diffusion (CD) and Mode-Seeking Region Growing (MSRG) algorithms. These hot spots seen in PET are then confirmed and more accurately segmented considering CT information, through the Joint Likelihood Ratio Test technique for probabilistic integration. Experiments show that the proposed multi-modal method achieves more accurate and reproducible tumour delineation than using PET or CT alone. Copyright © 2012 Inderscience Enterprises Ltd.
Keywords: computerized tomography; medical imaging; tumors; segmentation; pet; ct; biomedical engineering; image segmentation; hidden markov model; likelihood ratio test; tumour delineation; HMM; whole body; information fusion; region growing; likelihood ratio tests; hidden markov models; polyethylene terephthalates
Journal Title: International Journal of Biomedical Engineering and Technology
Volume: 8
Issue: 2-3
ISSN: 1752-6418
Publisher: Inderscience Publishers  
Date Published: 2012-01-01
Start Page: 182
End Page: 199
Language: English
DOI: 10.1504/IJBET.2012.046085
PROVIDER: scopus
DOI/URL:
Notes: --- - "Export Date: 4 June 2012" - "Source: Scopus"
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  1. Yulin Song
    116 Song