Automated Organ Detection in Water-Fat Separated Magnetic Resonance Imaging
Thomas Demarcy 1 , Axel Saalbach 2 , and Julien Sngas 2
Ecole des Mines, Saint-Etienne, France,
Research Laboratories, Hamburg, Germany
To cope with todays healthcare challenges of providing
cost-effective care with constant quality, advanced
image analysis techniques that automatically extract
anatomical information from complex, large image
datasets are required. In this work, computer vision
techniques based on trained classifiers and Haar-like
features were extended to 3D and applied to
automatically detect and localize a number of target
organs in 3D water-fat separated, whole-body MR images.
The benefit of using the joint information provided by
water and fat separation was investigated.
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