Research on benign and malignant masses classification in mammogram
WEI Jie
CAO Xuyang
CHEN Houjin
LI Yanfeng
Abstract：The classification of mammographic masses into malignant or benign is one of the important contents in CAD (Computer-Aided Diagnosis) systems.In this paper,mass contour segmentation and mass classification under different features are studied.Based on the idea of maximizing the between-cluster variance of the segmented images,a modified marker controlled watershed segmentation algorithm is proposed and employed to give the coarse segmentation.Then CV (Active Contour without Edge) model is used to refine the coarse segmentation.The classification performance of existing shape features and texture features under different classifiers is tested for the purpose of validating how different features perform in the malignant-benign classification.The proposed method is evaluated on a public database,DDSM (Digital Database for Screening Mammography).The results show that automatic segmentation can get texture features with better classification performances.
Keywords：information processingmasses classificationmasses segmentationwatershed algorithm
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 73-78 )