Multilevel learning-based segmentation of ill-defined and spiculated masses in mammograms

Medical Physics

Volumn 37, Issue 11, 2010, Pages 5993-6002

  Tao, Yimo ^a,b   Lo, Shih Chung B ^b   Freedman, Matthew T ^b   Makariou, Erini ^b   Xuan, Jianhua ^a  

^a State University   (United States)

^b GEORGETOWN UNIVERSITY MEDICAL CENTER   (United States)

Author keywords

breast cancer; breast masses; image segmentation; mammography

Indexed keywords

CLUTTER (INFORMATION THEORY); GRAPHIC METHODS; MAMMOGRAPHY; MEDICAL IMAGING; PIXELS; TEXTURES;

BACKGROUND CLUTTER; BREAST CANCER; BREAST MASS; CONDITIONAL PROBABILITIES; LEARNING-BASED APPROACH; LEARNING-BASED SEGMENTATION; SEGMENTATION RESULTS; STATISTICAL MODELING;

IMAGE SEGMENTATION;

EID: 78149438156     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.3490477     Document Type: Article

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