title: Knowledge-based 3D analysis from 2D medical images.
abstract: An anatomical knowledge-based system for image analysis that interprets CT/MR (computed tomography/magnetic resonance) images of the human chest cavity is reported. The approach utilizes a low-level image analysis system with the ability to analyze the data in bottom-up (or data-driven) and top-down (or model-driven) modes to improve the high-level recognition process. Several image segmentation algorithms, including K-means clustering, pyramid-based region extraction, and rule-based merging, are used for obtaining the segmented regions. To obtain a reasonable number of well-segmented regions that have a good correlation with the anatomy, a priori knowledge in the form of masks is used to guide the segmentation process. Segmentation of the brain is also considered.
authors.affiliation: Dept. of Electr. and Comput. Eng., Cincinnati Univ., OH.
authors.forename: A P
authors.initials: AP
authors.lastname: Dhawan
authors.forename: L
authors.initials: L
authors.lastname: Arata