多重声像图特征对恶性肿瘤的分类

Subarna Chatterjee, A. Ray, Rezaul Karim, A. Biswas
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引用次数: 1

摘要

乳腺癌是女性中最常见的癌症,也是世界上仅次于肺癌的第二大癌症。在本文中,我们提出了一种诊断算法,该算法使用超声的多种特征来识别乳腺结节恶性肿瘤,以提供更好的适当治疗机会。采用多层感知器形式的人工神经网络来生成预测模型。本文利用MATLAB对该算法进行了仿真,并给出了仿真结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of malignant tumors using multiple sonographic features
Breast cancer is the most common form of cancer among women and the second one in the world trailing behind lung cancer. In this paper, we present a diagnostic algorithm that uses multiple features of ultra-sonography for identifying breast nodule malignancy to provide better chance of a proper treatment. An artificial neural network has been put into operation in the form of multilayer perceptron to generate the predictive model. MATLAB has been used for the simulation of this algorithm and the results obtained are presented in this paper.
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