Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

O. Pauly, B. Glocker, A. Criminisi, D. Mateus, A. Martinez-Möller, S. Nekolla, N. Navab
Fast Multiple Organs Detection and Localization in Whole-Body MR Dixon Sequences
To appear in Proc. Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011), Toronto, Canada, September 2011 (bib)

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 multidimensional 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 much improved anatomy localization accuracy with higher efficiency and robustness.
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