An Efficient Approach for Automated Mass Segmentation and Classification in Mammograms

Journal of Digital Imaging

Volumn 28, Issue 5, 2015, Pages 613-625

  Dong, Min ^a   Lu, Xiangyu ^a   Ma, Yide ^a   Guo, Yanan ^a   Ma, Yurun ^a   Wang, Keju ^a  

^a LANZHOU UNIVERSITY   (China)

Author keywords

Automated mass segmentation; Classification; Computer aided detection; Mammography; Random forest

Indexed keywords

AUTOMATION; COMPUTER AIDED DIAGNOSIS; DATA MINING; DATABASE SYSTEMS; DECISION TREES; DISEASES; GENETIC ALGORITHMS; IMAGE RETRIEVAL; IMAGE SEGMENTATION; MAMMOGRAPHY; PARTICLE SWARM OPTIMIZATION (PSO); SUPPORT VECTOR MACHINES; VECTORS; X RAY SCREENS;

BREAST CANCER DIAGNOSIS; CLASSIFICATION TECHNIQUE; COMPUTER AIDED DETECTION; CORRELATION COEFFICIENT; GENETIC ALGORITHM SUPPORT VECTOR MACHINES; MASS SEGMENTATION; RANDOM FORESTS; VECTOR FIELD CONVOLUTIONS;

CLASSIFICATION (OF INFORMATION);

ALGORITHM; BREAST TUMOR; COMPUTER ASSISTED DIAGNOSIS; DECISION TREE; DIAGNOSTIC IMAGING; FACTUAL DATABASE; FEMALE; HUMAN; MAMMOGRAPHY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE;

ALGORITHMS; BREAST NEOPLASMS; DATABASES, FACTUAL; DECISION TREES; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAMMOGRAPHY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE;

EID: 84941998220     PISSN: 08971889     EISSN: 1618727X     Source Type: Journal    
DOI: 10.1007/s10278-015-9778-4     Document Type: Article

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