@inproceedings{simonyan2012immediate,
author = {Simonyan, K. and Modat, M. and Ourselin, S. and Criminisi, A. and Zisserman, A. and Criminisi, Antonio},
title = {Immediate ROI Search for 3D Medical Images},
booktitle = {MICCAI workshop on Medical Content-based Retrieval for Clinical Decision Support (MCBR-CDS)},
year = {2012},
month = {October},
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 [9], and it is shown that the learnt ranking function outperforms the baseline.},
url = {http://approjects.co.za/?big=en-us/research/publication/immediate-roi-search-for-3d-medical-images/},
edition = {MICCAI workshop on Medical Content-based Retrieval for Clinical Decision Support (MCBR-CDS)},
}