Abstract

This paper presents a knowledge-based method for automatic reconstruction and recognition of pulmonary blood vessels from chest x-ray CT images with 10-mm thickness. The system has four main stages: (1) automatic extraction and segmentation of blood vessel components from each 2-D image, (2) analysis of these components, (3) a search for points connecting blood vessel segments in different CT slices, using a knowledge base for 3-D reconstruction, and (4) object manipulation and display. The authors also describe a method of representing 3-D anatomical knowledge of the pulmonary blood vessel structure. The edges of blood vessels in chest x-ray images are unclear, in contrast to those in angiograms. Each CT slice has thickness, and blood vessels are slender, so a simple graphical display, which can be used for bone tissues from CT images, is not sufficient for pulmonary blood vessels. It is therefore necessary to use anatomical knowledge to track the blood vessel lines in 3-D spaces. Experimental results using actual images of a normal adult male has shown that utilizing anatomical information enables one to improve processing efficiency and precision, such as blood vessel extraction and searching for connecting points.© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call