Bayesian and grAphical models for biomedical imaging [electronic resource] : first International Workshop, BAMBI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers / M. Jorge Cardoso, Ivor Simpson, Tal Arbel, Doina Precup, Annemie Ribbens (eds.).

Bayesian and grAphical models for biomedical imaging [electronic resource] : first International Workshop, BAMBI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers / M. Jorge Cardoso, Ivor Simpson, Tal Arbel, Doina Precup, Annemie Ribbens (eds.).

9783319122892 electronic book
3319122894 electronic book
9783319122885

Cham : Springer, 2014.

English

1 online resource (x, 131 pages) : illustrations.

10.1007/978-3-319-12289-2 doi

TA1637

621.36/7

This book constitutes the refereed proceedings of the First International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2014, held in Cambridge, MA, USA, in September 2014 as a satellite event of the 17th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2014. The 11 revised full papers presented were carefully reviewed and selected from numerous submissions with a key aspect on probabilistic modeling applied to medical image analysis. The objectives of this workshop compared to other workshops, e.g. machine learning in medical imaging, have a stronger mathematical focus on the foundations of probabilistic modeling and inference. The papers highlight the potential of using Bayesian or random field graphical models for advancing scientific research in biomedical image analysis or for the advancement of modeling and analysis of medical imaging data.

Incldues author index.

Access limited to authorized users.

Online resource; title from PDF title page (SpringerLink, viewed October 10, 2014).

Lecture notes in computer science ; 8677.
LNCS sublibrary. SL 1, Theoretical computer science and general issues.

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