Cargando…
Dependence of Shape-Based Descriptors and Mass Segmentation Areas on Initial Contour Placement Using the Chan-Vese Method on Digital Mammograms
Variation in signal intensity within mass lesions and missing boundary information are intensity inhomogeneities inherent in digital mammograms. These inhomogeneities render the performance of a deformable contour susceptible to the location of its initial position and may lead to poor segmentation...
Autores principales: | Acho, S. N., Rae, W. I. D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4561378/ https://www.ncbi.nlm.nih.gov/pubmed/26379762 http://dx.doi.org/10.1155/2015/349874 |
Ejemplares similares
-
Chan–Vese Reformulation for Selective Image Segmentation
por: Roberts, Michael, et al.
Publicado: (2019) -
Brain Tumor Segmentation Based on Bendlet Transform and Improved Chan-Vese Model
por: Meng, Kexin, et al.
Publicado: (2022) -
Local shape descriptors for neuron segmentation
por: Sheridan, Arlo, et al.
Publicado: (2022) -
Automatic Breast Mass Segmentation and Classification Using Subtraction of Temporally Sequential Digital Mammograms
Publicado: (2022) -
Blurred Palmprint Recognition Based on Stable-Feature Extraction Using a Vese–Osher Decomposition Model
por: Hong, Danfeng, et al.
Publicado: (2014)