Region-based active surface modelling and alpha matting for unsupervised tumour segmentation in PET

ICIP(2012)

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摘要
This paper presents a combination of existing advanced methods to solve the partial volume segmentation problem. It uses region-based active surface modelling in a hierarchical scheme to eliminate segmentation errors, followed by an alpha matting step to further refine the segmentation. This method can have an interest in several applications in medical imaging. We have validated our method on real PET images of head-and-neck cancer patients as well as custom designed phantom PET images. Experiments show that our method can generate more accurate segmentation than existing approaches.
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关键词
region-based active surface modelling,segmentation error elimination,head-and-neck cancer patients,image segmentation,alpha matting modelling,hierarchical scheme,pet,unsupervised tumour segmentation,medical imaging applications,partial volume segmentation problem,cancer,positron emission tomography,tumours,solid modelling,custom designed phantom pet images,tumour segmentation,3d active surface modelling,phantoms,medical image processing,alpha matting
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