Cargando…
Automatic Detection and Classification of Breast Tumors in Ultrasonic Images Using Texture and Morphological Features
Due to severe presence of speckle noise, poor image contrast and irregular lesion shape, it is challenging to build a fully automatic detection and classification system for breast ultrasonic images. In this paper, a novel and effective computer-aided method including generation of a region of inter...
Autores principales: | Su, Yanni, Wang, Yuanyuan, Jiao, Jing, Guo, Yi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bentham Open
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158436/ https://www.ncbi.nlm.nih.gov/pubmed/21892371 http://dx.doi.org/10.2174/1874431101105010026 |
Ejemplares similares
-
Effect of zooming on texture features of ultrasonic images
por: Kakkos, Stavros K, et al.
Publicado: (2006) -
A Benign and Malignant Breast Tumor Classification Method via Efficiently Combining Texture and Morphological Features on Ultrasound Images
por: Wei, Mengwan, et al.
Publicado: (2020) -
Variable Selection from Image Texture Feature for Automatic Classification of Concrete Surface Voids
por: Zhao, Ziting, et al.
Publicado: (2021) -
Automatic detection of COVID-19 using pruned GLCM-Based texture features and LDCRF classification
por: Bakheet, Samy, et al.
Publicado: (2021) -
Automatic detection of pneumonia in chest X-ray images using textural features
por: Ortiz-Toro, César, et al.
Publicado: (2022)