首页> 外文会议>2018 International Conference on Advancement in Electrical and Electronic Engineering >Detection Classification of Tumor Cells from Bone MR Imagery Using Connected Component Analysis Neural Network
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Detection Classification of Tumor Cells from Bone MR Imagery Using Connected Component Analysis Neural Network

机译:使用连接成分分析和神经网络从骨MR图像中检测和分类肿瘤细胞

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Bone cancer is a class of diseases that are characterized by an unfettered growth of the cell and it is considered to be the main reasons of early death around the globe. Therefore, early detection and classification of the bone tumor are become needed to cure the patient. This study uses a connected component labeling algorithm for the detection of the bone tumor. In this work, the artificial neural network (ANN) is used for the classification of bone tumor. Total 220 bone MR images of previously verified patients are collected and the texture features of this images are used for the training and testing of the neural network. The obtained performance of the classification result exhibit that the neural network provides 92.50% success rate in bone tumor classification.
机译:骨癌是一类以细胞不受限制的生长为特征的疾病,被认为是全球范围内早期死亡的主要原因。因此,需要对骨肿瘤进行早期检测和分类以治愈患者。这项研究使用连接的组件标记算法来检测骨肿瘤。在这项工作中,人工神经网络(ANN)用于骨肿瘤的分类。总共收集了220例先前验证过的患者的MR图像,并将这些图像的纹理特征用于神经网络的训练和测试。所获得的分类结果性能表明,神经网络在骨肿瘤分类中提供了92.50%的成功率。

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