Immediate ROI search for 3-D medical images

Conference item

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.

Authors: Simonyan, K; Modat, M; Ourselin, S; Cash, D; Criminisi, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer
• Host title: Medical Content-Based Retrieval for Clinical Decision Support: Third MICCAI International Workshop, MCBR-CDS 2012, Nice, France, October 1st, 2012, Revised Selected Papers
• Pages: 56–67
• Series: Lecture Notes in Computer Science
• Series number: 7723
• Place of publication: Berlin / Heidelberg
• Publication date: 2013-02-20
• Event title: Third MICCAI International Workshop, MCBR-CDS 2012
• Event location: Nice, France
• Event start date: 2012-10-01
• Event end date: 2012-10-01
• DOI: 10.1007/978-3-642-36678-9_6
• EISSN: 1611-3349
• ISSN: 0302-9743
• EISBN: 9783642366789
• ISBN: 9783642366772
• Language: English
• Keywords: ROI; immediate structured search; exemplarbased registration; learning to rank; visual search