2^nd Workshop on GRaphs in biomedicAl Image anaLysis (GRAIL 2018)

20^thSeptember 2018, Granada, Spain

Call for Paper

Graph-based models have been developed for a wide variety of problems in computer vision and biomedical image analysis. Applications ranging from segmentation, registration, classification, and shape modelling, to population analysis have been successfully encoded through graph structures, demonstrating the versatile and principled nature of the graph based approaches.

Graphs are powerful mathematical structures which provide a flexible and scalable framework to model objects and their interactions in a readily interpretable fashion. As a consequence, an important body of work has been developed around different methodological aspects of graph including, but not limited to, graphical models, graph-theoretical algorithms, spectral graph analysis, graph dimensionality reduction, and graph-based network analysis. However, new topics are also emerging as the outcome of interdisciplinary studies, shedding light on areas like deep structured models and signal processing on graphs.

Topics of Interest :

• Probabilistic graphical models for biomedical image analysis
• Discrete and continuous optimization for graphical models
• Signal processing on graphs for biomedical image analysis
• Deep/machine learning on structured and unstructured graphs
• Convolutional neural networks on graphs
• Graphs for large scale population analysis
• Graph-based shape modeling and dimensionality reduction
• Combining imaging and non-imaging data through graph structures
• Graph-based generative models for biomedical image analysis
• Graph spectral methods
• Algorithms on graphs
• Graphs in neuroimaging
• Applications of graph-based models and algorithms to biomedical image analysis tasks (segmentation, registration, classification, etc.)

Important Dates

Submission Deadline	:	11 June 2018
Authors Notification	:	10 July 2018
Final Manuscript Due	:	11 July 2018

 

User Name : john
Posted 26-05-2018 on 17:27:36 AEDT

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