Advantages and Application Prospects of Deep Learning in Image Recognition and Bone Age Assessment
HU TING-HONG1,2, WAN LEI2, LIU TAI-ANG3, WANG MAO-WEN2, CHEN TENG1, WANG YA-HUI2
（1. Department of Forensic Science, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; 2. Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China; 3. Shanghai Fanyang Information Technology Co., LTD., Shanghai 200444, China）
Abstract： 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.