| Revue: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560596 |
| ISSN: | 1405-5546 |
| Autores: | Touami, Rachida1 Benamrane, Nacéra1 |
| Instituciones: | 1Université des Sciences et de la Technologie d'Oran Mohamed Boudiaf, Faculté des Mathématiques et d'Informatique, Oran. Argelia |
| Año: | 2021 |
| Periodo: | Abr-Jun |
| Volumen: | 25 |
| Número: | 2 |
| Paginación: | 369-379 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | Breast cancer is the most typical form of cancer among the female population and the most common form of cancer-related death. However, if the cancer is detected at an early stage, treatment may be more effective. Mammography is one of the most used imaging modalities for the early breast cancer diagnosis. The present paper proposes an intelligent system for the detection and analysis of microcalcifications in mammography using the region growing algorithm, the particle swarm optimization algorithm (PSO), and the Probabilistic neural network (PNN) to detect the presence of breast cancer as early as possible and to avoid resorting to ablation of the breast. |
| Keyword: | Breast cancer, Mammography, Microcalcification, Region growing segmentation, Particle swarm optimization, Probabilistic neural network |
| Texte intégral: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
