A Learning Dynamic Discrimination Technique (LDDT) for Identifying Cancer in Histological Breast Images
Abstract
Many female die due to breast cancer making it a leading cause of mortality in women. Early diagnosis and treatment of the disease becomes imperative for improving survival rates and reducing morbidity. Pathologists diagnose breast cancer with irregularities in cell shapes or densities. Manual pathological processes are cumbersome and error-prone. Recently, CAD systems (Computer-aided-diagnosis)have been employed for early identification of breast cancers. A new semi-automated cell classification system for effectively identifying cancerous breast cells has been proposed. The proposed technique called LDDT achieves its desired classifications efficiently. The accuracy of the technique is checked using F-Measure.