Knowledge-based segmentation and correspondence of vascular structures from biplane angiograms

Ying Sun

doi:10.1117/12.18912

1 July 1990 Knowledge-based segmentation and correspondence of vascular structures from biplane angiograms

Ying Sun

Proceedings Volume 1233, Medical Imaging IV: Image Processing; (1990) https://doi.org/10.1117/12.18912
Event: Medical Imaging '90, 1990, Newport Beach, CA, United States

Abstract

A combined signal processing and knowledge-based approach was developed to graphically reconstruct the three-dimensional vascular structures from dual biplane angiograms. It was shown that the correct correspondence of segments between two orthogonal views of a simple tree model can be determined by use of a knowledge base containing a directed-graph representation of the tree structures a procedure of recognizing crossover points a requirement of consistency in connectivity and a constraint of coordinate invariance along the axis of view rotation. However the current system failed to handle errors in the segmentation caused by either the complexity of the vascular structures or the presence of noise in the images. The result suggested that the key to resolving ambiguities in the two-view reconstruction problem be the provision for extensive interactions among segmentation correspondence and knowledge base. An systematic analysis and a preliminary design of such a knowledge-based system were presented. 1.

Citation Download Citation

Ying Sun "Knowledge-based segmentation and correspondence of vascular structures from biplane angiograms", Proc. SPIE 1233, Medical Imaging IV: Image Processing, (1 July 1990); https://doi.org/10.1117/12.18912

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available