Toward breast cancer diagnosis based on automated segmentation of masses in mammograms

Pattern Recognition

Volumn 42, Issue 6, 2009, Pages 1138-1148

  Rojas Domínguez, Alfonso ^a   Nandi, Asoke K ^a  

^a UNIVERSITY OF LIVERPOOL   (United Kingdom)

Author keywords

Breast cancer; Breast masses; Image analysis; Mammography

Indexed keywords

AUTOMATION; CLASSIFIERS; DIAGNOSIS; DIAGNOSTIC RADIOGRAPHY; FEATURE EXTRACTION; IMAGE ANALYSIS; LEARNING SYSTEMS; MEDICAL IMAGING; PROGRAMMING THEORY; SUPPORT VECTOR MACHINES;

AUTOMATED SEGMENTATION METHODS; AUTOMATED SEGMENTATIONS; BACKGROUND REGIONS; BAYESIAN CLASSIFIERS; BREAST CANCER; BREAST CANCER DIAGNOSIS; BREAST MASSES; CLASSIFICATION PERFORMANCE; COEFFICIENT OF VARIATIONS; FEATURE-BASED; FISHER'S LINEAR DISCRIMINANTS; FOREGROUND REGIONS; GRADIENT ORIENTATIONS; HIGH SPECIFICITIES; LOW SENSITIVITIES; MALIGNANT MASS; MAMMOGRAPHY; REGION-GROWING; SCREENING PROGRAMS; SEGMENTATION METHODS; SEGMENTATION QUALITIES; SIGNATURE INFORMATIONS; SUPPORT VECTORS;

PROGRAM DIAGNOSTICS;

EID: 59149100526     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2008.08.006     Document Type: Article

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