Estimation of discontinuous optical flow using a neural network for echocardiographic images

Vincent Devlaminck; L. Lelaurin; A. Yacoubi; Jean-Paul Dubus

doi:10.1117/12.208716

12 May 1995 Estimation of discontinuous optical flow using a neural network for echocardiographic images

Vincent Devlaminck, L. Lelaurin, A. Yacoubi, Jean-Paul Dubus

Proceedings Volume 2434, Medical Imaging 1995: Image Processing; (1995) https://doi.org/10.1117/12.208716
Event: Medical Imaging 1995, 1995, San Diego, CA, United States

Abstract

The purpose is to develop a method of estimation of the field of vectors velocity to evaluate motion of the heart in view of an assistance with the medical diagnosis. This method is based on an application of neural network to optical flow estimation in a sequence of echocardiographic images. The network is discrete, deterministic and locally connected. It contains redundant neurons for representing w_(i,j)x and w_(i,j)y the components of the velocity vector at point (i,j). We formulate the motion estimation problem as one of minimizing an error function of three terms. The first term is a least-squares penalty expression which coerce the flow field into satisfying the flow equation; the second is a smoothness constraint used for obtaining a smooth optical flow and the third term is a line process to weaken the smoothness constraint and to detect motion discontinuities. The minimization of this function is obtained with the help from a neural network. The model consist of 2*L*M Hopfield sub-networks for an image of size L*M. Each sub-network is totally interconnected. Results provide a good coherence between the homogeneous area cartography of motion and textured regions present in the image.

Citation Download Citation

Vincent Devlaminck, L. Lelaurin, A. Yacoubi, and Jean-Paul Dubus "Estimation of discontinuous optical flow using a neural network for echocardiographic images", Proc. SPIE 2434, Medical Imaging 1995: Image Processing, (12 May 1995); https://doi.org/10.1117/12.208716

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