Coverart for item
The Resource Bayesian and grAphical models for biomedical imaging : 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 : 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.)

Label
Bayesian and grAphical models for biomedical imaging : first International Workshop, BAMBI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers
Title
Bayesian and grAphical models for biomedical imaging
Title remainder
first International Workshop, BAMBI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers
Statement of responsibility
M. Jorge Cardoso, Ivor Simpson, Tal Arbel, Doina Precup, Annemie Ribbens (eds.)
Title variation
BAMBI 2014
Creator
Contributor
Editor
Editor of compilation
Subject
Genre
Language
eng
Summary
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
Member of
Cataloging source
GW5XE
Dewey number
621.36/7
Illustrations
illustrations
Index
index present
LC call number
TA1637
Literary form
non fiction
http://bibfra.me/vocab/lite/meetingDate
2014
http://bibfra.me/vocab/lite/meetingName
BAMBI (Workshop)
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
  • Cardoso, M. Jorge
  • Simpson, Ivor
  • Arbel, Tal
  • Precup, Doina
  • Ribbens, Annemie
Series statement
  • Lecture Notes in Computer Science,
  • LNCS sublibrary. SL 1, Theoretical computer science and general issues
Series volume
8677
http://library.link/vocab/subjectName
  • Image analysis
  • Bioinformatics
  • Bioinformatics
  • Image analysis
  • Engineering & Applied Sciences
  • Computer Science
Label
Bayesian and grAphical models for biomedical imaging : 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.)
Instantiates
Publication
Note
Includes author index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Intro; Preface; Organization; Table of Contents; N3 Bias Field Correction Explained as a Bayesian Modeling Method; 1 Introduction; 2 Methods; 2.1 The N3 Method in Its Practical Implementation; 2.2 EM-Based Bias Field Estimation; 2.3 N3 as an Approximate MAP Parameter Estimator; 3 Experiments; 4 Results; 5 Discussion; References; A Bayesian Approach to Distinguishing Interdigitated Muscles in the Tongue from Limited Diffusion Weighted Imaging; 1 Introduction; 2 Methods; 2.1 Multi-tensor Model with a Fixed Tensor Basis; 2.2 Mixture Fraction Estimation with Prior Knowledge; 3 Experiments
  • 3.1 Digital Phantom3.2 In Vivo Tongue Diffusion Data; 4 Discussion; 5 Conclusion; References; Segmentation and Tracking of E. coli; 1 Introduction; 2 Microscopic Setup and Data Preprocessing; 3 Segmentation Methods; 3.1 Thresholding and Component Trees (CT); 3.2 Parametric Max-Flow (PMF); 3.3 Parametric Max-Flow and Random Forest (PMFRF); 4 A Graphical Model for Segmentation and Tracking; 4.1 Costs; 4.2 Constraints; 4.3 Eliminating Segmentation Variables; 4.4 Finding The Globally Optimal Solution; 5 Results; 6 Summary and Discussion; References
  • Physiologically Informed Bayesian Analysis of ASL fMRI Data1 Introduction; 2 A Physiologically Informed ASL/BOLD Link; 2.1 The Extended Balloon Model; 2.2 Physiological Linear Relationship between Response Functions; 3 Bayesian Hierarchical Model for ASL Data Analysis; 4 A Physiologically Informed 2-steps Inference Procedure; 4.1 Hemodynamics Estimation Step M1; 4.2 Perfusion Response Estimation Step M2; 5 Simulation Results; 6 Real Data Results; 7 Discussion and Conclusion; References
  • Bone Reposition Planning for Corrective Surgery Using Statistical Shape Model: Assessment of Differential Geometrical Features1 Introduction; 2 SSM Based Planning; 2.1 Fitting of the SSM to Two Bone Segements; 2.2 Probability Distribution Functions for Shape Validity and Scaling; 2.3 Probability Distribution Model to Compare Shapes; 3 Experiments; 3.1 Data; 3.2 Evaluating the SSM; 3.3 Evaluating Modes of Variation; 3.4 Including the Geometrical Features; 3.5 Accuracy of Bone Repositioning; 4 Discussion; 5 Appendix; An Inference Language for Imaging; 1 Introduction; 2 Methods
  • 2.1 The Modeling Language2.2 The Inference Engine; 3 Motion-aware Positron Emission Tomography; 4 Conclusion; 5 Download; References; An MRF-Based Discrete Optimization Framework for Combined DCE-MRI Motion Correction and Pharmacokinetic Parameter Estimation; 1 Introduction; 2 Methods; 2.1 Data Cost Calculation Using Pharmacokinetic Model Prediction; 2.2 Optimization on the Reduced 4D Graph; 3 Results; 3.1 Algorithm Evaluation on Synthetic Data; 3.2 Pharmacokinetic Modelling and Motion Correction on DCE-MRI Images of Rectal Cancer; 4 Discussion and Conclusion; 5 Future Work; References
Control code
892732549
Dimensions
unknown
Extent
1 online resource (x, 131 pages)
File format
unknown
Form of item
online
Isbn
9783319122892
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-319-12289-2
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)892732549
Label
Bayesian and grAphical models for biomedical imaging : 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.)
Publication
Note
Includes author index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Intro; Preface; Organization; Table of Contents; N3 Bias Field Correction Explained as a Bayesian Modeling Method; 1 Introduction; 2 Methods; 2.1 The N3 Method in Its Practical Implementation; 2.2 EM-Based Bias Field Estimation; 2.3 N3 as an Approximate MAP Parameter Estimator; 3 Experiments; 4 Results; 5 Discussion; References; A Bayesian Approach to Distinguishing Interdigitated Muscles in the Tongue from Limited Diffusion Weighted Imaging; 1 Introduction; 2 Methods; 2.1 Multi-tensor Model with a Fixed Tensor Basis; 2.2 Mixture Fraction Estimation with Prior Knowledge; 3 Experiments
  • 3.1 Digital Phantom3.2 In Vivo Tongue Diffusion Data; 4 Discussion; 5 Conclusion; References; Segmentation and Tracking of E. coli; 1 Introduction; 2 Microscopic Setup and Data Preprocessing; 3 Segmentation Methods; 3.1 Thresholding and Component Trees (CT); 3.2 Parametric Max-Flow (PMF); 3.3 Parametric Max-Flow and Random Forest (PMFRF); 4 A Graphical Model for Segmentation and Tracking; 4.1 Costs; 4.2 Constraints; 4.3 Eliminating Segmentation Variables; 4.4 Finding The Globally Optimal Solution; 5 Results; 6 Summary and Discussion; References
  • Physiologically Informed Bayesian Analysis of ASL fMRI Data1 Introduction; 2 A Physiologically Informed ASL/BOLD Link; 2.1 The Extended Balloon Model; 2.2 Physiological Linear Relationship between Response Functions; 3 Bayesian Hierarchical Model for ASL Data Analysis; 4 A Physiologically Informed 2-steps Inference Procedure; 4.1 Hemodynamics Estimation Step M1; 4.2 Perfusion Response Estimation Step M2; 5 Simulation Results; 6 Real Data Results; 7 Discussion and Conclusion; References
  • Bone Reposition Planning for Corrective Surgery Using Statistical Shape Model: Assessment of Differential Geometrical Features1 Introduction; 2 SSM Based Planning; 2.1 Fitting of the SSM to Two Bone Segements; 2.2 Probability Distribution Functions for Shape Validity and Scaling; 2.3 Probability Distribution Model to Compare Shapes; 3 Experiments; 3.1 Data; 3.2 Evaluating the SSM; 3.3 Evaluating Modes of Variation; 3.4 Including the Geometrical Features; 3.5 Accuracy of Bone Repositioning; 4 Discussion; 5 Appendix; An Inference Language for Imaging; 1 Introduction; 2 Methods
  • 2.1 The Modeling Language2.2 The Inference Engine; 3 Motion-aware Positron Emission Tomography; 4 Conclusion; 5 Download; References; An MRF-Based Discrete Optimization Framework for Combined DCE-MRI Motion Correction and Pharmacokinetic Parameter Estimation; 1 Introduction; 2 Methods; 2.1 Data Cost Calculation Using Pharmacokinetic Model Prediction; 2.2 Optimization on the Reduced 4D Graph; 3 Results; 3.1 Algorithm Evaluation on Synthetic Data; 3.2 Pharmacokinetic Modelling and Motion Correction on DCE-MRI Images of Rectal Cancer; 4 Discussion and Conclusion; 5 Future Work; References
Control code
892732549
Dimensions
unknown
Extent
1 online resource (x, 131 pages)
File format
unknown
Form of item
online
Isbn
9783319122892
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-319-12289-2
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)892732549

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