@inproceedings {365,
	title = {Indirect knowledge-based approach to non-rigid multi-modal registration of medical images},
	booktitle = {20th Canadian Conference on Electrical and Computer Engineering},
	year = {2007},
	abstract = {<p>Information acquired using different medical imaging techniques (e.g., MRI, PET, CT, etc.) can be combined to get a clear understanding of the overall condition of a patient for the purpose of diagnosis. Registering images from different modalities without a priori knowledge is difficult since the images may have very different intensity mappings and structural characteristics. This paper presents a novel approach to the multi-modal registration of medical images through the use of a priori knowledge to align medical images using an indirect mapping. The proposed algorithm uses stored information from successful alignment results to infer a relationship between the input images from different modalities. This relationship is then used to estimate the transformations needed to align the medical images together. Experimental results show that a high level of accuracy can be achieved using the proposed algorithm to align medical images from different modalities.</p>
},
	keywords = {biomedical MRI, CT, image registration, indirect knowledge-based approach, knowledge engineering, medical image processing, medical images, medical imaging techniques, MRI, nonrigid multimodal image registration, patient diagnosis, PET, positron emission tomography},
	doi = {http://dx.doi.org/10.1109/CCECE.2007.298},
	author = {A Wong and W Bishop}
}
