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

机译:用于妇女代谢性骨疾病分类的高精度Deep-CNN框架

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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,由于钙缺乏,女性容易患上各种代谢性骨疾病,如骨质疏松症,骨质疏松症,软化症,佩吉特氏病等。现有的工作无法从X射线图像中动态学习骨骼的一般特征,并且无法准确地对代谢性骨疾病进行分类。因此,本文提出了一种嵌入深层的卷积神经网络体系结构,该体系结构能够以较高的准确度和较低的误差值对骨骼疾病进行显着分类。

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