Detection of microcalcifications clusters in mammograms through TS-MRF segmentation and SVM-based classification

Proceedings - International Conference on Pattern Recognition

Volumn 3, Issue , 2004, Pages 742-745

  D'Elia, C ^a   Marrocco, C ^a   Molinara, M ^a   Poggi, G ^b   Scarpa, G ^b   Tortorella, F ^a  

^a UNIVERSITY OF CASSINO AND SOUTHERN LAZIO   (Italy)

^b UNIVERSITY OF NAPLES FEDERICO II   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

BREAST CANCER; DIGITAL MAMMOGRAMS; MARKOV RANDOM FIELD (MRF) MODEL; MICROCALCIFICATION;

CALCIFICATION (BIOCHEMISTRY); COMPUTER AIDED ANALYSIS; FUZZY SETS; IMAGE SEGMENTATION; MARKOV PROCESSES; MATHEMATICAL MODELS; MEDICAL IMAGING; RADIOLOGY; RELIABILITY; TREES (MATHEMATICS);

MAMMOGRAPHY;

EID: 10044274214     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2004.1334635     Document Type: Conference Paper

References (6)

1. N. Karssemeijer, "Adaptive Noise Equalization and Recognition of Microcalcification Clusters in Mammograms", International Journal of Pattern Recognition and Artificial Intelligence, vol. 7, 1993, pp. 1357-1376.
2. C. D'Elia, G. Poggi and G. Scarpa, "A Tree-Structured Markov Random Field Model for Bayesian Image Segmentation", IEEE Trans. on Image Processing, vol. 12, no. 10, 2003, pp. 1259-1273.
3. N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines, Cambridge Univ. Press, 2000.
4. T. Joachims, "Making large-scale SVM learning practical", in B. Schölkopf, C.J.C. Burges, A.J. Smola, eds., Advances in Kernel Methods, MIT Press, 1999, pp. 169-184.
5. T. Netsch and H. Peitgen, "Scale-Space Signatures for the Detection of Clustered Microcalcifications in Digital Mammograms", IEEE Trans. on Medical Imaging, vol. 18, no. 9, 1999, pp. 774-786.
6. H.D. Cheng, J. Wang and X. Shi, "Microcalcification Detection Using Fuzzy Logic and Scale Space Approach", Pattern Recognition, vol. 37, 2004, pp. 363-375.