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

Y. Chiou, F. Lure, P. Ligomenides
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引用次数: 1

Abstract

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.<>
混合肺结节检测(HLND)系统中的神经知识库目标检测
针对噪声图像环境下的目标检测问题,提出了一种基于人工神经网络结构和交互式知识库系统的“混合肺结节检测系统”。本文介绍了该系统的结构及其在肺癌肺放射学中结节的检测和分类中的应用。HLND系统的配置包括以下处理阶段:(1)预处理,增强图背景对比度;(2)基于形态学的基于结节最显著特征的结节目标嫌疑人快速选择;(3)特征空间确定和基于神经网络的怀疑域约简;(4)交互知识库与知识融合处理,最终分类结节可疑场。本文还报道了该方法的初步结果。
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