A neural network based integrated image processing environment for object recognition in medical applications

J. A. Ware, I. Ciuca
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引用次数: 4

Abstract

The paper outlines an integrated image processing environment that uses neural networks for object recognition and classification. The image processing environment which is Windows based, encapsulates a multiple-document interface (MDI) and is menu driven. Object (shape) parameter extraction is focused on features that are invariant in terms of translation, rotation and scale transformations. The neural network models incorporated into the environment allow both clustering and classification of objects from the analysed image. Mapping neural networks perform input sensitivity analysis on the extracted feature measurements and thus facilitates the removal of irrelevant features and improvements in the degree of generalisation.
一种基于神经网络的综合图像处理环境,用于医学目标识别
本文概述了一种利用神经网络进行目标识别和分类的集成图像处理环境。该图像处理环境是基于Windows的,封装了一个多文档接口(MDI)并由菜单驱动。物体(形状)参数的提取重点是在平移、旋转和尺度变换方面不变的特征。将神经网络模型整合到环境中,允许从分析图像中对对象进行聚类和分类。映射神经网络对提取的特征测量值进行输入灵敏度分析,从而有助于去除无关特征并提高泛化程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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