Computer aided detection of microcalcifications in digital mammograms using a synthetic technique

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 4875, Issue 2, 2002, Pages 639-644

  Wang, Ruiping ^a   Wan, Baikun ^a   Ma, Zhenghe ^a   Cao, Xuchen ^b  

^a TIANJIN UNIVERSITY   (China)

^b TIANJIN MEDICAL UNIVERSITY   (China)

Author keywords

AND operation; Computer aided detection; Difference image; Wavelet based denoising

Indexed keywords

ALGORITHMS; MAMMOGRAPHY; MEDICAL IMAGING; ONCOLOGY; RADIOLOGY; SPURIOUS SIGNAL NOISE; TUMORS;

BREAST CANCER; COMPUTER AIDED DETECTION; DETECTION ALGORITHM; DIGITAL MAMMOGRAMS; FALSE-POSITIVE DETECTION; MICROCALCIFICATIONS; SYNTHETIC TECHNIQUE; WAVELET BASED NOISE SUPPRESSION;

COMPUTER AIDED DIAGNOSIS;

EID: 0036452682     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.477210     Document Type: Conference Paper

References (14)

1. Heng-Da cheng, Yui Man Liu and Rita I. Freimanis, "A novel approach to microcalcifications detection using fuzzy logic techniques," IEEE Trans. Med. Imag., Vol.17, no.1, pp. 442-450,June.1998.
2. William Mark Morrow, Raman Bhalachandra Paranjape, Rangaraj, M, et al. "Region-Based Contrast Enhancement of Mammograms," IEEE Trans. Med. Imag. Vol.11, no.3, pp.392-406, Sep.1992.
3. Giuseppe Boccignone, Angelo Chianese and Antonio Picariello, "Computer Aided Detection of Microcalcifications in Digital Mammograms," Computers in Biology and Medicine, Vol.30, pp. 267-286, 2000.
4. Robin N.Strickland, Hee Hahn, "Wavelet transforms for detecting microcalcifications in mammograms," IEEE. Trans. Med. Imag. VOL.5, no.2, pp. 218-229, Apr. 1996.
5. N. Karssemeijer, "Recognition of Clustered Microcalcifications Using A Random Field Model, biomedical image processing and biomedical visualization," SPIE Proc., Vol. 1905, pp.776-786, 1993.
6. N. Karssemeijer, "Adaptive Noise Equalization and Recognition of Microcalcification Clusters in Mammograms," Inter. J. Pattern Recognit. Artificial Intell., Vol.7, no.6, pp.1357-1376, 1993.
7. N.Karssemeijer, "A Stochasic Model for Automated Detection of Calcifications in Digital Mammograms," Image Vision Comput., Vol.10, no.6,pp. 369-375, 1992.
8. Xiao-Hui wang, Bin Zheng, Walter F. Good, et al, "Computer-assisted diagnosis of breast cancer using a data-driven Bayesian belief network," International Journal of medical informatics, Vol.54, pp.115-126, 1999.
9. Brijesh, Verma, "A neural network based techniques to locate and classify microcalcifications in digital mammograms," Proceedings of IEEE World Congress on Computational Intelligence, pp. 2163-2168, Anchorage, USA, May 1998.
10. Nishikawa, R, Gier, M. Doi K, Vyborny C and Schmidt R, "Computer-aided detection and diagnosis of masses and clustered microcalcifications from digital mammograms," State of the art in digital mammographic image analysis, K W Bowyer & S Astley, Vol. 9, pp.82-102, World scientific Publishing, London, 1994.
11. Fogel David B, Wasson III, Eugene C, et al, "Evolving artificial neural networks for screening features from mammograms," Artificial Intelligence in Medicine, Vol.14, no.3, pp.317-326, Nov. 1998.
12. Songyang Yu and Ling Guan, "A CAD System for the Automatic Detection of Clustered Microcalcifications in Digitized Mammogram Films," IEEE Trans. Med. Imag., Vol.19, no.2, pp.115-126, 2000.
13. Brijesh Verma and John Zakos, "A Computer-Aided Diagnosis System For Digital Mammograms Based On Fuzzy-Neural And Feature Extraction Techniques," IEEE Trans. on Information Technology in Biomedicine, Vol.5, pp.46-54, 2000.
14. Rioul and M. Vetterli, "Wavelets and signal processing", IEEE signal processing Magazine, Vol.11, pp. 14-38, Oct. 1991.