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 language||English (US)|
|Number of pages||18|
|Journal||International Journal of Biomedical Engineering and Technology|
|State||Published - 2012|
All Science Journal Classification (ASJC) codes
- Biomedical Engineering