A generic approach to organ detection using 3D haar-like features

Automatic segmentation of medical images requires accurate detection of the desired organ as a first step. In contrast to application specific approaches, learning-based object detection algorithms are easily adaptable to new applications. We present a learning-based object detection approach based on the Viola-Jones algorithm. We propose several extensions to the original approach, including a new 3D feature type and a multi-organ detection scheme. The algorithm is used to detect six different organs in CT scans as well as the prostate in MRI data. Our evaluation shows that the algorithm provides fast and reliable detection results in all cases.