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Medical Image Understanding and Analysis Conference 2014

Authors: Reyes-Aldasoro, Constantino Carlos; Slabaugh, Greg;

Medical Image Understanding and Analysis Conference 2014

Abstract

MIUA 2014 is the eighteenth in the series of annual meetings. Since its inauguration, in 1997 at Oxford, this multidisciplinary event has been providing a forum for presenting and discussing research related to medical image analysis. The areas covered by MIUA include computer science, mathematics, engineering and physics as well as biosciences, medical research and clinical practice. The principal research interest of the conference is in methods of analysis that extract meaningful and quantitative information from images to aid diagnosis and therapy or to support research in fundamental biomedical sciences. Over the lifetime of the MIUA conferences we have seen significant advances made in the development of novel imaging modalities and methods. Many ideas first proposed by members of the medical imaging community have progressed from the research lab- oratory to clinical practice and are making direct impact on patient care. We are very pleased to host a conference in London that contributes to these endeavours. This years keynote lectures are delivered by three eminent academics: Professor David Hawkes from University College London, Professor Jean-Christophe Olivo-Marin from Institut Pasteur, and Professor Roger Gunn from Imperial College London. We are very grateful for their contributions. The conference prides itself in providing a friendly forum and support for research students and young scientists. The organisers of the MIUA 2012 conference at Swansea initiated the idea of pre- conference tutorials aimed at introducing the participants to novel or emerging modalities or techniques by a leading expert in a field. This year we are grateful to Dr Jasmina Lazic of the Mathworks for a tutorial on MATLAB for Medical Image Processing, and Dr Antonio Criminisi, from Microsoft Research for a tutorial on Decision Forests in Medical Image Analysis. MIUA was originally conceived as a UK event, however, over the years international contributions from Europe and beyond have been increasing. This year we warmly welcome participants and contributors from France, Germany, Belgium, Portugal, Italy, Czech Republic, Greece, Cyprus, Austria, USA, South Africa, Saudi Arabia, Indonesia, Taiwan, and the Republic of Korea. There are many people whose effort and commitment contributed to the organisation of this conference and who deserve special thanks: The MIUA Steering Committee chaired by Bill Crum, for their unfailing support and advice. The reviewers, for their thoughtful comments and timely submission of paper reviews. Emma Leaver, Louise Gordon, Kristie Loutsiou, and Razina Patel for enthusiastic, and frequent, help with administration. Jack Lewis and Stephanie Schaal for maintaining the MIUA 2014 website. All the students, staff and session chairs, for their help before and during the conference. Professor Roger Crouch, for formally opening the conference. The British Machine Vision Association, for sponsoring bursaries for the best student papers. The School of Mathematics, Engineering, and Computer Science at City University London for sponsoring the conference. John Wiley & Sons, for sponsoring prizes. The British Association for Cancer Research, for sponsoring a best student prize in cancer. Finally, many thanks go to the authors and presenters of the papers and to all the con- ference delegates for their scientific contributions, and through participation, for helping to maintain a healthy and vibrant medical image analysis community.

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Keywords

Medical Imaging, Medical Image Analysis, Medical Image Computing, Computational Pathology

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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