Bone mineral density value evaluation based on photoacoustic spectral analysis combined with deep learning method  

作　　者：Xue Zhou Zhibin Jin Ting Feng Qian Cheng Xueding Wang Yao Ding Hongchen Zhan Jie Yuan 周雪;金志斌;封婷;程茜;王学鼎;丁尧;詹洪陈;袁杰(Jinling College,Nanjing University,Nanjing 210089,China;School of Electronic Science and Engineering,Nanjing University,Nanjing 210008,China;Nanjing Drum Tower Hospital,Nanjing 210093,China;Institution of Acoustics,Tongji University,Shanghai 200092,China)

机构地区：[1]Jinling College,Nanjing University,Nanjing 210089,China [2]School of Electronic Science and Engineering,Nanjing University,Nanjing 210008,China [3]Nanjing Drum Tower Hospital,Nanjing 210093,China [4]Institution of Acoustics,Tongji University,Shanghai 200092,China

出　　处：《Chinese Optics Letters》2020年第4期63-66,共4页中国光学快报（英文版）

基　　金：supported by the National Key Research and Development Program of China(No.2017YFC0111402);the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.19KJB510031);the Natural Science Foundation of Jiangsu Province(No.BK20181256)。

摘　　要：The diagnosis of osteoporosis is eventually converted to the measurement of bone mineral density(BMD)in clinical trials.Since our previous work had proved the ability of using photoacoustic spectral analysis(PASA)to efficiently detect osteoporosis,in this contribution,we proposed a fully connected multi-layer deep neural network combined with PASA to semi-quantify BMD values corresponding to varying degrees of bone loss and to further evaluate the degree of osteoporosis.Experiments were carried out on swine femur heads,and the performance of our proposed method is satisfying for future clinical screening.

关 键 词：PHOTOACOUSTICS OSTEOPOROSIS neural network 

分 类 号：R580[医药卫生—内分泌] TP18[医药卫生—内科学]