title: A new method based on both fuzzy set and possibility theories for tumor volume segmentation on PET images.
abstract: A new automatic method for tumor volume segmentation on PET images has been developed. The method introduced in this paper is based on previous works in MRA segmentation and involves both fuzzy set and possibility theories. Visual results prove the method efficiency which is confirmed by obtained Jaccard index.
authors.affiliation: Inserm, U703, University Hospital of Lille, France. a-dewalle@chru-lille.fr
authors.forename: A S
authors.initials: AS
authors.lastname: Dewalle-Vignion
authors.forename: N
authors.initials: N
authors.lastname: Betrouni
authors.forename: N
authors.initials: N
authors.lastname: Makni
authors.forename: D
authors.initials: D
authors.lastname: Huglo
authors.forename: J
authors.initials: J
authors.lastname: Rousseau
authors.forename: M
authors.initials: M
authors.lastname: Vermandel
mesh_terms: D000465:Algorithms; D001331:Automation; D006528:Carcinoma, Hepatocellular / Q000473:pathology; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D017143:Fuzzy Logic; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008113:Liver Neoplasms / Q000473:pathology; D008962:Models, Theoretical; D009369:Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D049268:Positron-Emission Tomography / Q000379:methods*; D011336:Probability; D015203:Reproducibility of Results