Rapid Diagnosis of Fatty Liver by Glossoscopy Based on Spectrometry
LI Gang1, ZHAO Jing1, ZHANG Jing1, HU Guang-qin2, LU Xiao-zuo2, LIN Ling1*
1. State Key Laboratory of Precision Measurement Technology and Intruments, Tianjin University, Tianjin 300072, China 2. Institute of Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China
Abstract：In order to diagnose fatty liver noninvasively, rapidly and accurately, this article presented a new method based on spectroscopy to diagnose fatty liver. This method is non-invasive, rapid. Because tongue can objectively reflect physiological and pathological changes, so this experiment collected reflectance spectrum on the tongue tips of volunteers at first, then analyzed the above data, calculated the normalized reflection ratio, and built a three-layer BP network model. Thirty two healthy people and 44 fatty liver sufferers were chosen randomly from the total 115 samples and their data were input into neural network, then the data of unknown samples of 14 healthy and 25 fatty liver ones were input into the model, and the classification accuracy was 89.7%. This result approved the feasibility of using spectroscopy to diagnose fatty liver. Meanwhile, the result showed that spectral method can reflect the information of organization and tiny circulation taken by tongue more objectively. This method may provide a fast and simple diagnostic tools for clinic, and also can provide a reference to the syndrome measurement of the traditional Chinese medicine.
李 刚1，赵 静1，张 晶1，胡广芹2，陆小左2，林 凌1* . 基于光谱法舌诊的脂肪肝快速诊断 [J]. 光谱学与光谱分析, 2010, 30(10): 2748-2751.
LI Gang1, ZHAO Jing1, ZHANG Jing1, HU Guang-qin2, LU Xiao-zuo2, LIN Ling1* . Rapid Diagnosis of Fatty Liver by Glossoscopy Based on Spectrometry . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2010, 30(10): 2748-2751.
[1] ZHANG Wen-yuan, MA Lin(张文缓, 马 琳). Chinese Journal of Coal Industry Medicine(中国煤炭工业医学杂志), 2008, 11(2): 280. [2] Thijssen J M, Starke A, Weijers G, et al. Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 2008, 55(6): 1343. [3] Icer S, Lkizceli T, Coskun A, et al. Evaluation of Fatty Liver Ultrasonography Images. in 14th National Biomedical Engineering Meeting (BIYOMUT ’09). Iemir, Balcova, 20, May, 2009. 1. [4] LIN Rongho. Artificial Intelligence in Medicine, 2009, 47(1): 53. [5] LI Guo-kuan, LUO Yu, DENG Wei, et al. Computer Diagnosis of Fatty Liver Ultrasonic Images Based on Support Vector Machine. in 30th Annual International Conference on Engineering in Medicine and Biology Society (EMBS ’08) of IEEE, Vancouver, British Columbia, 20-25, Aug., 2008. 4768. [6] YANG Xiao, CHAO Zhang. 2-D Hybrid Transform and Feature Extracting Algorithm of Eatty Liver Ultrasonic Images. in 9th International Conference on Signal Processing (ICSP ’08), Beijing, 26-29, Oct., 2008. 2174. [7] WANG Li-jie, CAI Li-juan, ZHOU Zhen, et al(王丽杰,蔡丽娟, 周 真，等). Infrared Technology(红外技术)，2008, 30(9): 546. [8] LIU Huan-jun, ZHANG Bo, WANG Zong-ming, et al(刘焕军，张 柏，王宗明，等). Journal of infrared and Millimeter Waves(红外与毫米波学报), 2008, 27(2): 138. [9] ZHU Shi-ping, WANG Gang, YANG Fei, et al(祝诗平, 王 刚, 杨 飞, 等). Journal of Infrared and Millimeter Waves(红外与毫米波学报), 2008, 27(2): 129. [10] LEI Cun-xi, LIU Chang-hui, DONG Meng(雷存喜, 刘长辉, 董 萌). Chinese Journal of Spectroscopy Laboratory(光谱实验室), 2009, 26(6): 1609. [11] TIAN Jian, JIN Li-hong, ZHAO Li-hui, et al(田 坚, 金丽红, 赵丽辉, 等). Journal of Changchun University of Science and Technology(Natural Science Edition)(长春理工大学学报·自然科学版), 2008, 31(4): 1. [12] LI Gang, WANG Yan, LI Qiu-xia, et al(李 刚, 王 焱, 李秋霞, 等). Journal of Infrared and Millimeter Waves(红外与毫米波学报), 2006, 25(5): 345. [13] SHANG Yong-hui, LI Hua, SUN Jia-juan, et al(尚永辉, 李 华, 孙家娟, 等). Chinese Journal of Spectroscopy Laboratory(光谱实验室), 2009, 26(6): 1413. [14] SU Rong-guo, LIANG Sheng-kang, ZHU Chen-jian, et al(苏荣国, 梁生康, 祝陈坚, 等). Environmental Science and Technology(环境科学与技术), 2008, 31(3): 52.
