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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Fast Multiple Organ Detection and Localization in Whole-Body MR Dixon Sequences
verfasst von : Olivier Pauly, Ben Glocker, Antonio Criminisi, Diana Mateus, Axel Martinez Möller, Stephan Nekolla, Nassir Navab
Erschienen in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011
Verlag: Springer Berlin Heidelberg
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Automatic localization of multiple anatomical structures in medical images provides important semantic information with potential benefits to diverse clinical applications. Aiming at organ-specific attenuation correction in PET/MR imaging, we propose an efficient approach for estimating location and size of multiple anatomical structures in MR scans. Our contribution is three-fold: (1) we apply supervised regression techniques to the problem of anatomy detection and localization in whole-body MR, (2) we adapt random ferns to produce multi-dimensional regression output and compare them with random regression forests, and (3) introduce the use of 3D LBP descriptors in multi-channel MR Dixon sequences. The localization accuracy achieved with both fern- and forest-based approaches is evaluated by direct comparison with state of the art atlas-based registration, on ground-truth data from 33 patients. Our results demonstrate improved anatomy localization accuracy with higher efficiency and robustness.