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

被引：0

作者：

Navada, Dinesh K. R. ^{[1
]}

Ganesh, S. ^{[1
]}

Bhargavi, K. ^{[1
]}

机构：

[1] Siddaganaga Inst Technol, Dept CSE, Tumkur, Karnataka, India

来源：

PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON COMMUNICATION AND ELECTRONICS SYSTEMS (ICCES 2018) | 2018年

关键词：

CNN; Metabolic bone disease; X-ray; Pooling; Precision; Women; Calcium deficiency;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：147 / 152

页数：6

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