Paper Info
Title
Multi-atlas synthesis for computer assisted diagnosis: Application to cardiovascular diseases
Abstract
Atlas-based analysis methods rely on the morphological similarity between the atlas and target images, and on the availability of labelled images. Problems can arise when the deformations introduced by pathologies affect the similarity between the atlas and a patient's image. The aim of this work is to exploit the morphological dissimilarities between atlas databases and pathological images to diagnose the underlying clinical condition, while avoiding the dependence on labelled images. To this end, the proposed method is formulated under the principle of atlas-based segmentation but, instead of propagating labels, we propagate image intensities. Using a set of MR atlas databases, each database associated with a clinical condition, synthetic images are generated for a target image. The diagnosis is established by assessing the degree of similarity between the synthetic images and the target and assigning the condition of the top-ranked synthetic image. The obtained results are comparable to state-of-the-art methods using annotated images, with an accuracy of 90.0% when evaluated on a set of 60 whole heart MR images containing healthy and pathological subjects.
Year
DOI
Venue
2015
10.1109/ISBI.2015.7163870
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)
Keywords
Field
DocType
Computer-aided diagnosis,image synthesis,MR,heart
Computer vision,Degree of similarity,Pattern recognition,Medical imaging,Segmentation,Computer science,Computer-aided diagnosis,Image segmentation,Image synthesis,Atlas (anatomy),Artificial intelligence
Conference
ISSN
Citations 
PageRank 
1945-7928
1
0.35
References 
Authors
6
4
Name
Order
Citations
PageRank
Maria A. Zuluaga127925.84
Ninon Burgos29411.64
Andrew Taylor3142.77
Sébastien Ourselin42499237.61