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

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.<>