A method for extracting and recognizing thoracic organ regions from three-dimensional (3D) CT chest images has been proposed in this paper. This method can be simply described as a pixel-labelling process, that is, each pixel in a chest CT image is attached with a predefined label that indicates a special organ or tissue of human body. The density distribution and strength of connectivity of different organ regions have been investigated and used for the recognition process. We developed a system to visualize the 3D CT images based on volume rendering technique and intergraded this method into it. We found that with the recognition results we can view the shape of a special organ without any overlap and can understand the relationship of human organs more clearly and easily.