Immediate ROI search for 3-d medical images

Authors:
Karen Simonyan;Marc Modat;Sebastien Ourselin;David Cash;Antonio Criminisi;Andrew Zisserman
Affiliations:
University of Oxford, UK;Centre for Medical Image Computing, University College London, UK;Centre for Medical Image Computing, University College London, UK;Centre for Medical Image Computing, University College London, UK;Microsoft Research, Cambridge, UK;University of Oxford, UK
Venue:
MCBR-CDS'12 Proceedings of the Third MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
Year:
2012

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Abstract

The objective of this work is a scalable, real-time, visual search engine for 3-D medical images, where a user is able to select a query Region Of Interest (ROI) and automatically detect the corresponding regions within all returned images. We make three contributions: (i) we show that with appropriate off-line processing, images can be retrieved and ROIs registered in real time; (ii) we propose and evaluate a number of scalable exemplar-based image registration schemes; (iii) we propose a discriminative method for learning to rank the returned images based on the content of the ROI. The retrieval system is demonstrated on MRI data from the ADNI dataset, and it is shown that the learnt ranking function outperforms the baseline.