A new method for robust organ positioning in CT images

Robust initialization is essential for any successful segmentation process of medical images. For CT images, initialization is challenging because quality, appearance, content, and field-of-view of the images are highly variable. Furthermore, high execution speed is desirable, whereas the user tolerance to errors is low in clinical applications. We present a new method for efficient and robust positioning of organs in CT images. It is based on a novel probabilistic atlas that, given a tissue type, describes the probability density of the random variable spatial location. Random sampling is then employed to select the most informative points for matching. We present results on pelvic and abdominal images acquired for radiotherapy planning.