Probabilistic Atlas-guided Eigen-organ Method for Simultaneous Bounding Box Estimation of Multiple Organs in Volumetric CT Images

We propose an approach for the simultaneous bounding box estimation of multiple organs in volumetric CT images. Local eigen-organ spaces are constructed for different types of training organs, and a global eigen-space, which describes the spatial relationships between the organs, is also constructed. Each volume of interest in the abdominal CT image is projected into the local eigen-organ spaces, and several candidate locations are determined. The final selection of the organ locations is made by projecting the set of candidate locations into the global eigen-space. A probabilistic atlas of organs is used to eliminate locations with low probability and to guide the selection of candidate locations. Evaluation by the leave-one-out method using 10 volumetric abdominal CT images showed that the proposed method provided an average accuracy of 80.38% for 11 different organ types.