基于人工神经网络的医学图像融合肿瘤检测

D. Vasanthi, U. Palani, M. Vishnupriya, K. Saundariya
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引用次数: 0

摘要

在医学图像融合中,来自多种成像模式的图像被组合在一起,以提供对给定医学现象的准确分析。它有助于提高图像的质量,从而减少冗余。这些医学图像的融合有助于医生诊断和评估医学障碍,从而帮助他们提供必要的治疗。本文主要研究了利用人工神经网络对医学图像进行分解和特征提取。人工神经网络由人工神经元组成,人工神经元是连接单元或节点的集合。这些节点被用来松散地模拟生物大脑中的神经元。本文提出的算法利用该算法实现图像融合,降低了计算复杂度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Tumor by Fusing Medical Images using Artificial Neural Network
In Medical Image fusion, images from multiple imaging modalities are combined together to render accurate analysis of a given medical phenomenon. It helps in increasing the quality of the image thus reducing redundancy. The fusion of these medical images assists the medics in diagnosing and evaluating the medical hindrance and thereby helps them in providing the necessary treatment. This paper focuses on decomposition and feature extraction of the medical images using Artificial Neural Network (ANN). Artificial Neural Network consists of artificial neurons which are the collection of connected units or nodes. These nodes are used to loosely model the neurons in the biological brain. The proposed algorithm reduces the computational complexity by employing it to achieve image fusion.
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