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A High Precision Deep-CNN Framework for Classification of Metabolic Bone Diseases Among Women

机译:高精度深层CNN框架,用于妇女代谢骨病分类

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Nowadays women are prone to a variety of metabolic bone diseases like osteoporosis, osteopetrosis, osteomalacia, paget's disease etc. due to calcium deficiency. The existing works fail to dynamically learn generic features of bone from the X-ray image and precisely classify the metabolic bone diseases. So, in this paper a convoluted neural network architecture embedded with deep layers is proposed which significantly classifies the bone diseases with high precision and a lowered error value.
机译:如今,妇女易患了骨质疏松症,骨质病,骨质症,骨癌,Paget疾病等各种代谢骨病。由于钙缺乏症。现有工程未能动态地从X射线图像动态学习骨的普通特征,并精确地分类代谢骨病。因此,在本文中,提出了一种具有深层嵌入深层的复杂神经网络架构,从而显着对骨病具有高精度和降低的误差值。

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