000 | 03206nam a22006135i 4500 | ||
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001 | 978-3-319-12289-2 | ||
003 | DE-He213 | ||
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007 | cr nn 008mamaa | ||
008 | 140922s2014 gw | s |||| 0|eng d | ||
020 |
_a9783319122892 _9978-3-319-12289-2 |
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024 | 7 |
_a10.1007/978-3-319-12289-2 _2doi |
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_aBayesian and grAphical Models for Biomedical Imaging _h[electronic resource] : _bFirst International Workshop, BAMBI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers / _cedited by M. Jorge Cardoso, Ivor Simpson, Tal Arbel, Doina Precup, Annemie Ribbens. |
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2014. |
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300 |
_aX, 131 p. 54 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes in Computer Science, _x0302-9743 ; _v8677 |
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520 | _aThis 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. | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aAlgorithms. | |
650 | 0 |
_aComputer science _xMathematics. |
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650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aComputer graphics. | |
650 | 0 | _aImage processing. | |
650 | 0 | _aPattern recognition. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aAlgorithm Analysis and Problem Complexity. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
650 | 2 | 4 | _aImage Processing and Computer Vision. |
650 | 2 | 4 | _aPattern Recognition. |
650 | 2 | 4 | _aComputer Graphics. |
650 | 2 | 4 | _aDiscrete Mathematics in Computer Science. |
700 | 1 |
_aCardoso, M. Jorge. _eeditor. |
|
700 | 1 |
_aSimpson, Ivor. _eeditor. |
|
700 | 1 |
_aArbel, Tal. _eeditor. |
|
700 | 1 |
_aPrecup, Doina. _eeditor. |
|
700 | 1 |
_aRibbens, Annemie. _eeditor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783319122885 |
830 | 0 |
_aLecture Notes in Computer Science, _x0302-9743 ; _v8677 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-12289-2 |
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