Work on B-SCREEN

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Conferences and Events

Upcoming

Past

Meetings

Schedule

  • 17 January 2008 (11:00) - ICIS
  • 20 December 2007 (11:00) - UMCN
  • 6 December 2007 (11:00) - ICIS
  • 23 November 2007 (11:00) - UMCN
  • 19 July 2007 (11:00) - UMCN
  • 21 June 2007 (11:00) - UMCN
  • 24 May 2007 (11.00) - ICIS
  • 10 May 2007 (11.15) - UMCN
  • 3 May 2007 (11.15) - ICIS
  • 19 April 2007 (11.15) - UMCN
  • 5 April 2007 (11.15 14:00) - UMCN
  • 29 March 2007 (11:15) - ICIS (postponed)
  • 22 March 2007 (11:15) - UMCN (postponed)
  • 08 March 2007 (11:15) - ICIS

Minutes

Technical Notes

Experiments

Relevant papers

Baysian networks for CAD Systems

  • M. Samulski, Classification of Breast Lesions in Digital Mammograms, Master's Thesis. Radboud University Nijmegen, June 2006. (PDF)

Other CAD Systems

  • S. Timp, Analysis of Temporal Mammogram Pairs to Detect and Characterise Mass Lesions, PhD in medical sciences, Radboud University Nijmegen, 2006. (PDF)
  • S. van Engeland, Detection of mass lesions in mammograms by using multiple views, PhD thesis, Radboud University Nijmegen, 2006. (PDF)
  • G. te Brake, Computer Aided Detection of Masses in digital mammograms, Defended 11-01-2000, KUN; Prom. prof.dr. C.C.A.M. Gielen, dr.ir. N. Karssemeijer. (PDF)
  • B. Kovalerchuk, E. Vityaev, J.F. Ruiz, Consistent and Complete Data and "Expert" Mining in Medicine, In: Medical Data Mining and Knowledge Discovery, Springer, 2001, pp. 238-280. (PDF)

Bayesian networks and Logic

  • K. Kersting and L. de Raedt, Bayesian Logic Programs, Technical Report n.151, Institute for Computer Science, University of Freiburg, 2001. (PDF)
  • D. Fierens and H. Blockeel and M. Bruynooghe and J. Ramon, Logical Bayesian Networks and Their Relation to Other Probabilistic Logic Models, Proceedings of the 15th International Conference on Inductive Logic Programming (ILP), 2005. (PDF)
  • N. Landwehr and K. Kersting and L. de Raedt, nFOIL: Integrating Naive Bayes and FOIL, Proceedings of the 20th National Conference on Artificial Intelligence (AAAI), 2005. (PDF)
  • J. Davis, E. Burnside, I. Dutra, D. Page and V. S. Costa, An Integrated Approach to Learning Bayesian Networks of Rules, Proceedings of the European Conference of Machine Learning (ECML), 2005. (PDF)
  • J. Davis, E. Burnside, I. Dutra, D. Page, R. Ramakrishnan, V. S. Costa and J. Shavlik, View Learning for Statistical Relational Learning: With an Application to Mammography. Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI), 2005. (PDF)

Reports on Screening Mammography

  • J.J. Fenton, S.H. Taplin, P.A. Carney, L. Abraham, E.A. Sickles, C. D’Orsi, E.A. Berns, G. Cutter, R. Edward Hendrick, W.E. Barlow, and J.G. Elmore, Influence of Computer-Aided Detection on Performance of Screening Mammography, The New England Journal of Medicine, vol.356, no.14, April 2007 (PDF)
  • F.M. Hall, Breast Imaging and Computer-Aided Detection, Editorials, The New England Journal of Medicine, vol.356, no.14, April 2007 (PDF)

Linking mammographic regions

  • S. van Engeland, S. Timp and N. Karssemeijer, Finding corresponding regions of interest in mediolateral oblique and craniocaudal mammographic views, Medical Physics, vol. 33, no. 9, pp. 3203-12, September 2006 (PDF)
  • S. van Engeland and N. Karssemeijer, Combining two mammographic projections in a computer aided mass detection method, Medical Physics, vol. 34, no. 3, pp. 898-905, March 2007 (PDF)

Mass segmentation

  • S. Timp and N. Karssemeijer, A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography, Medical Physics, vol. 31, no. 5, pp. 958-971, April 2004 (PDF)