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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Multi-organ Localization Combining Global-to-Local Regression and Confidence Maps
verfasst von : Romane Gauriau, Rémi Cuingnet, David Lesage, Isabelle Bloch
Erschienen in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014
Verlag: Springer International Publishing
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We propose a method for fast, accurate and robust localization of several organs in medical images. We generalize global-to-local cascades of regression forests [1] to multiple organs. A first regressor encodes global relationships between organs. Subsequent regressors refine the localization of each organ locally and independently for improved accuracy. We introduce
confidence maps
, which incorporate information about both the regression vote distribution and the organ shape through probabilistic atlases. They are used within the cascade itself, to better select the test voxels for the second set of regressors, and to provide richer information than the classical bounding boxes thanks to the shape prior. We demonstrate the robustness and accuracy of our approach through a quantitative evaluation on a large database of 130 CT volumes.