Cargando…
Head and Neck Cancer Tumor Segmentation Using Support Vector Machine in Dynamic Contrast-Enhanced MRI
OBJECTIVE: We aimed to propose an automatic method based on Support Vector Machine (SVM) and Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to segment the tumor lesions of head and neck cancer (HNC). MATERIALS AND METHODS: 120 DCE-MRI samples were collected. Five curve features and t...
Autores principales: | Deng, Wei, Luo, Liangping, Lin, Xiaoyi, Fang, Tianqi, Liu, Dexiang, Dan, Guo, Chen, Hanwei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5632988/ https://www.ncbi.nlm.nih.gov/pubmed/29114180 http://dx.doi.org/10.1155/2017/8612519 |
Ejemplares similares
-
Bayes Clustering and Structural Support Vector Machines for Segmentation of Carotid Artery Plaques in Multicontrast MRI
por: Guan, Qiu, et al.
Publicado: (2012) -
MRI Image Segmentation Model with Support Vector Machine Algorithm in Diagnosis of Solitary Pulmonary Nodule
por: Feng, Bo, et al.
Publicado: (2021) -
Dynamic Contrast-enhanced Magnetic Resonance Imaging for Differentiating Between Primary Tumor, Metastatic Node and Normal Tissue in Head and Neck Cancer
por: Chen, Liangliang, et al.
Publicado: (2018) -
Retracted: Bayes Clustering and Structural Support Vector Machines for Segmentation of Carotid Artery Plaques in Multicontrast MRI
por: Computational and Mathematical Methods in Medicine,
Publicado: (2014) -
Support Vector Machines
por: Deng, Naiyang
Publicado: (2012)