By Topic

Neural-knowledge base object detection in Hybrid Lung Nodule Detection (HLND) system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Chiou, Y.S.P. ; Caelum Res. Corp., Silver Spring, MD, USA ; Lure, F.Y.M. ; Ligomenides, P.A.

A “Hybrid Lung Nodule Detection (HLND) system” based on artificial neural network architecture and interactive knowledge-base system is developed for object detection in noisy image environments. This paper describes the system architecture and its application to detection and classification of nodules in lung cancerous pulmonary radiology. The configuration of the HLND system includes the following processing phases: (1) pre-processing to enhance the figure-background contrast; (2) Morphology based quick selection of nodule object suspects based upon the most prominent feature of nodules; and (3) feature space determination and neural network based suspect fields reduction; (4) interactive knowledge base and knowledge fusion processing and final classification of nodule suspect fields. Preliminary results from the approach are also reported

Published in:

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on  (Volume:7 )

Date of Conference:

27 Jun-2 Jul 1994