title: [Head and Neck Tumor Segmentation Based on Augmented Gradient Level Set Method].
abstract: To realize the accurate positioning and quantitative volume measurement of tumor in head and neck tumor CT images, we proposed a level set method based on augmented gradient. With the introduction of gradient information in the edge indicator function, our proposed level set model is adaptive to different intensity variation, and achieves accurate tumor segmentation. The segmentation result has been used to calculate tumor volume. In large volume tumor segmentation, the proposed level set method can reduce manual intervention and enhance the segmentation accuracy. Tumor volume calculation results are close to the gold standard. From the experiment results, the augmented gradient based level set method has achieved accurate head and neck tumor segmentation. It can provide useful information to computer aided diagnosis.
authors.forename: Qiongmin
authors.initials: Q
authors.lastname: Zhang
authors.forename: Jing
authors.initials: J
authors.lastname: Zhang
authors.forename: Mintang
authors.initials: M
authors.lastname: Wang
authors.forename: Ling
authors.initials: L
authors.lastname: He
authors.forename: Yi
authors.initials: Y
authors.lastname: Men
authors.forename: Jun
authors.initials: J
authors.lastname: Wei
authors.forename: Hua
authors.initials: H
authors.lastname: Haung
mesh_terms: D003936:Diagnosis, Computer-Assisted; D006258:Head and Neck Neoplasms / Q000473:pathology*; D006801:Humans; D014057:Tomography, X-Ray Computed; D047368:Tumor Burden