Principal component analysis, classifier complexity and robustness of sonographic breast lesion classification

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7260, Issue , 2009, Pages

  Drukker, K ^a   Gruszauskas, N P ^a   Giger, M L ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

Breast US; Classification and classifier design; Computer aided diagnosis; Principal component analysis

Indexed keywords

AREA UNDER THE ROC CURVE; BAYESIAN; BREAST LESION; BREAST US; CLASSIFICATION AND CLASSIFIER DESIGN; CLASSIFICATION PERFORMANCE; DATA SETS; HIDDEN UNITS; IMAGE FEATURES; LINEAR DISCRIMINANT ANALYSIS; LOWER BOUNDS; NEURAL NET; NON-INFERIORITY; NUMBER OF COMPONENTS; OPTIMAL NUMBER; P-VALUES; PRINCIPAL COMPONENTS; QUADRATIC DISCRIMINANT ANALYSIS; SONOGRAPHIC; TEST SETS; TRAINING DATASET; TRAINING SETS;

CLASSIFIERS; COMPUTER AIDED ANALYSIS; COMPUTER AIDED DIAGNOSIS; CONTROL THEORY; DISCRIMINANT ANALYSIS; IMAGE PROCESSING; LEARNING SYSTEMS; MEDICAL IMAGING; STATISTICAL TESTS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 66749129162     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.811341     Document Type: Conference Paper

References (6)

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2. K. Horsch, M. L. Giger, L. A. Venta, and C. J. Vyborny, "Computerized diagnosis of breast lesions on ultrasound," Med Phys 29, 157-164 (2002). (Pubitemid 34157988)
3. K. Horsch, M. L. Giger, L. A. Venta, and C. J. Vyborny, "Automatic segmentation of breast lesions on ultrasound," Med Phys 28, 1652-1659 (2001). (Pubitemid 32783208)
4. N. P. Gruszauskas, K. Drukker, M. L. Giger, C. A. Sennett, and L. L. Pesce, "Performance of breast ultrasound computeraided diagnosis: dependence on image selection," Acad Radiol 15, 1234-1245 (2008).
5. K. Drukker, M. L. Giger, C. J. Vyborny, and E. B. Mendelson, "Computerized detection and classification of cancer on breast ultrasound," Acad Radiol 11, 526-535 (2004). (Pubitemid 38533856)
6. N. P. Gruszauskas, K. Drukker, M.L Giger., R.F. Chang, and W.K. Moon, "Preliminary study of the accuracy of an automated segmentation algorithm for sonographic breast lesions across different patient populations", AAPM conference, (2008).