Cargando…
Retrieval of Brain Tumors by Adaptive Spatial Pooling and Fisher Vector Representation
Content-based image retrieval (CBIR) techniques have currently gained increasing popularity in the medical field because they can use numerous and valuable archived images to support clinical decisions. In this paper, we concentrate on developing a CBIR system for retrieving brain tumors in T1-weigh...
Autores principales: | Cheng, Jun, Yang, Wei, Huang, Meiyan, Huang, Wei, Jiang, Jun, Zhou, Yujia, Yang, Ru, Zhao, Jie, Feng, Yanqiu, Feng, Qianjin, Chen, Wufan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4894628/ https://www.ncbi.nlm.nih.gov/pubmed/27273091 http://dx.doi.org/10.1371/journal.pone.0157112 |
Ejemplares similares
-
Retrieval of Brain Tumors with Region-Specific Bag-of-Visual-Words Representations in Contrast-Enhanced MRI Images
por: Huang, Meiyan, et al.
Publicado: (2012) -
Content-Based Image Retrieval Using Spatial Layout Information in Brain Tumor T1-Weighted Contrast-Enhanced MR Images
por: Huang, Meiyan, et al.
Publicado: (2014) -
Longitudinal measurement and hierarchical classification framework for the prediction of Alzheimer’s disease
por: Huang, Meiyan, et al.
Publicado: (2017) -
Extraction of Lesion-Partitioned Features and Retrieval of Contrast-Enhanced Liver Images
por: Yu, Mei, et al.
Publicado: (2012) -
Variability of Gross Tumor Volume in Nasopharyngeal Carcinoma Using (11)C-Choline and (18)F-FDG PET/CT
por: Jiang, Jun, et al.
Publicado: (2015)