Automatic tumour delineation in whole body PET/CT images

作者：Huang Xiaolei^*; Zhu Yaoyao; Li Hongsheng; Guan Haiying; Potesil Vaclav; Song Yulin; Kubota Toshiro; Zhou Xiang Sean

来源：International Journal of Biomedical Engineering and Technology, 2012, 8(2-3): 182-199.

DOI：10.1504/IJBET.2012.046085

• CT
• HMM
• Likelihood ratio tests
• Region growing
• Whole body

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.

• 出版日期2012
• 单位Memorial Sloan-Kettering Cancer Center; Lehigh University