Automated Organ Detection in Water-Fat Separated Magnetic Resonance Imaging

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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