Classifier ensemble for mammography CAD system combining feature selection with ensemble learning

International Congress Series

Volumn 1281, Issue , 2005, Pages 1047-1051

  Nemoto, Mitsutaka ^a   Shimizu, Akinobu ^a   Kobatake, Hidefumi ^a   Takeo, Hideya ^b   Nawano, Shigeru ^c  

^a TOKYO UNIVERSITY OF AGRICULTURE AND TECHNOLOGY   (Japan)

^b FUJIFILM CORPORATION   (Japan)

^c NATIONAL CANCER CENTER HOSPITAL EAST   (Japan)

Author keywords

Abnormal shadows; Classifier; Ensemble learning; Feature selection; Mammography

Indexed keywords

EID: 33646453536     PISSN: 05315131     EISSN: None     Source Type: Book Series    
DOI: 10.1016/j.ics.2005.03.083     Document Type: Article

References (4)

1. Nemoto M., et al. Improvement of tumor detection performance in mammograms by the feature selection from a large number of features and proposal of fast feature selection method. The IEICE Transactions on Information and Systems, J88-D-II 2 (2005) 416-426
2. Duda R.O., et al. Pattern Classification. 2nd edition (2000), Wiley 471-482
3. Paul Viola, Michael Jones, Robust Real-time Object Detection, Second International Workshop on Statistical and Computational Theories of Vision (SCTV2001), 2001, Published on web: http://home.stat.ucla.edu/~sczhu/Workshops/SCTV2001.html.
4. Pudil P., et al. Floating search method for feature selection with nonmonotonic criterion functions. The 12th International Conference on Pattern Recognition (ICPR1994) (1994) 279-283