Automatic tumour delineation in whole body PET/CT images

Xiaolei Huang, Yaoyao Zhu, Hongsheng Li, Haiying Guan, Vaclav Potesil, Yulin Song, Toshiro Kubota, Xiang Sean Zhou

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)182-199
Number of pages18
JournalInternational Journal of Biomedical Engineering and Technology
Volume8
Issue number2-3
DOIs
StatePublished - 2012

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

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