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深度学习在图像识别及骨龄评估中的优势及应用前景 被引量:20

Advantages and Application Prospects of Deep Learning in Image Recognition and Bone Age Assessment
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摘要 深度学习以及神经网络模型是近年来机器学习及人工智能领域新的研究方向及热点问题。深度学习在图像识别、语音识别应用中已取得了突破性进展,在人脸识别、信息检索等领域也展示出独特优势,得到了广泛应用。骨骼X线图像显示黑白灰不同阶度的变化,具有黑白对比、层次差异的图像特征,基于深度学习在图像识别中的优势,我们将其与骨龄评估研究有机结合,旨在为构建法医学骨龄自动化评估系统提供基础性数据。本文综述了深度学习的基本概念及其网络结构,阐述了近年来深度学习在国内外不同研究领域图像识别中的研究进展,以及深度学习在骨龄评估中的优势及应用前景。 Deep learning and neural network models have been new research directions and hot issues in the fields of machine learning and artificial intelligence in recent years. Deep learning has made a breakthrough in the applications of image and speech recognitions, and also has been extensively used in the fields of face recognition and information retrieval because of its special superiority. Bone X-ray images express different variations in black-white-gray gradations, which have image features of black and white contrasts and level differences. Based on these advantages of deep learning in image recognition, we combine it with the research of bone age assessment to provide basic datum for constructing a forensic automatic system of bone age assessment. This paper reviews the basic concept and network architectures of deep learning, and describes its recent research progress on image recognition in different research fields at home and abroad, and explores its advantages and application prospects in bone age assessment.
出处 《法医学杂志》 CAS CSCD 2017年第6期629-634,639,共7页 Journal of Forensic Medicine
基金 国家自然科学基金资助项目(81571859 81102305 81401559) 上海市法医学重点实验室资助项目(17DZ2273200) 上海市司法鉴定专业技术服务平台资助项目(16DZ2290900)
关键词 法医人类学 骨骼年龄测定 综述 图像处理 计算机辅助 深度学习 神经网络(计算机) 图像识别 forensic anthropology age determination by skeleton review image processing, computer-as-sisted deep learning neural networks (computer) image recognition
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