计算机科学 ›› 2020, Vol. 47 ›› Issue (2): 102-105.doi: 10.11896/jsjkx.191100195
所属专题: 医学图像
刘晓彤,王伟,李泽禹,沈思婉,姜小明
LIU Xiao-tong,WANG Wei,LI Ze-yu,SHEN Si-wan,JIANG Xiao-ming
摘要: 对显微图像中的尿液有形成分包括红白细胞等进行分析,可以帮助医生对有肾脏和泌尿系统疾病的患者进行评估。针对无染色、无标记的尿液图像中红白细胞存在对比度低、边缘模糊等问题,提出一种基于改进BP神经网络的识别方法。首先,将遗传算法引入BP神经网络对网络权值和阈值进行优化,解决训练过程中网络容易陷入局部极值等问题,提高BP神经网络的识别精度;其次,使用动量梯度下降法消除网络在梯度下降中产生的摆动,加快网络的收敛,提高BP神经网络的学习速度。与基础BP神经网络相比,改进方法对红白细胞的识别准确度分别提高了6.9%和9.5%,且识别时间分别缩短了19.3s和42.1s;与CNN识别算法相比,改进算法对白细胞的识别准确度提高了1.7%;与SVM识别算法相比,改进算法对红白细胞的识别准确度分别提高了12.9%和12.7%。验证实验和对照实验的结果表明,改进方法能以较高的准确率和较快的速度实现红白细胞的识别。
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[1]LIANG Y X,KANG R,LIAN C Y,et al.An end-to-end system for automatic urinary particle recognition with convolutional neural network[J].Journal of Medical Systems,2018,42(9):165. [2]SOMMER C,GERLICH D W.Machine learning in cell biology-teaching computers to recognize phenotypes[J].Journal of Cell Science,2013,126(24):5529-5539. [3]TU L L.Urinary sediment cell classification recognition system based on SVM algorithm research[D].Wuhan:Wuhan University of Technology,2014. [4]MOLINA-CABELLO M A,LÓPEZ-RUBIO E,LUQUE-BAE-NA R M,et al.Blood cell classification using the hough transform and convolutional neural networks[M]∥Advances in Intelligent Systems and Computing.Cham:Springer International Publishing,2018:669-678. [5]LIU Y C,RICHARD D,ZHANG Y C.Research on Pan-real-time Problem of Medical Detection Based on BPNNs Recognition Algorithm[J].Computer Science,2018,45(6):307-313. [6]LI B,HAN C,BAI B.Hybrid approach for human posture recognition using anthropometry and BP neural network based on Kinect V2[J].EURASIP Journal on Image and Video Proces-sing,2019(1):1-15. [7]WU Z P,ZHAO Y L,LUO Z L,et al.License plate recognition technology based on PSO-BP neural network[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2017,56(1):46-52. [8]LI D J,LI Y Y,LI J X,et al.Gesture recognition based on BP neural network improved by chaotic genetic algorithm[J].International Journal of Automation and Computing,2018,15(3):267-276. [9]CHENG H X,LIU J L.Application of BP neural network optimized by genetic algorithm in handwritten numeral recognition[J].Electronic Measurement Technology,2019,42(9):89-92. [10]PAN J H,WANG Y H,WU W.Physical quantity regression method based on optimized BP neural network[J].Computer Science,2018,45(12):170-176. [11]YOGANAND A V,KAVIDA A C,RUKMANIDEVI.Face detection approach from video with the aid of KPCM and improved neural network classifier[J].Multimedia Tools and Applications,2018,77(24):31763-31785. [12]ELSALAMONY H A.Detection of anaemia disease in human red blood cells using cell signature,neural networks and SVM[J].Multimedia Tools and Applications,2018,77(12):15047-15074. [13]XIAO M H,MA Y,FENG Z X,et al.Rice blast recognition based on principal component analysis and neural network[J].Computers and Electronics in Agriculture,2018,154:482-490. [14]DAI K K,ZHAO J W,CAO F L.A novel algorithm of extended neural networks for image recognition[J].Engineering Applications of Artificial Intelligence,2015,42:57-66. [15]BADI H,HAMZA A,HASAN S.New method for optimization of static hand gesture recognition[C]∥2017 Intelligent Systems Conference (IntelliSys).IEEE,2017:542-544. [16]WANG J C,YU Y,YANG K,et al.Brain tumor segmentation of MRI based on BP neural network[J].Journal of Biomedical Engineering Research,2016,35(4):290-293. [17]SUN Y,XUE B,ZHANG M,et al.Automatically Designing CNN Architectures Using Genetic Algorithm for Image Classification[J].arXiv:1808.03818,2018. [18]YAN X,LI S Y,ZHANG Z.Application of BP neural network based on genetic algorithms in prediction model of City water consumption[J].Computer Science,2016,43(S2):547-550. [19]LI Y M.The research of the urinary sediment images automatic recognition algorithm[D].Chongqing:Chongqing University,2007. [20]ADEM K.Exudate detection for diabetic retinopathy with circular Hough transformation and convolutional neural networks[J].Expert Systems With Applications,2018,114:289-295. [21]MU N,XU X,ZHANG X L,et al.Salient object detection using a covariance-based CNN model in low-contrast images[J].Neural Computing and Applications,2018,29(8):181-192. [22]OU X F,YAN P C,HE W,et al.Adaptive GMM and BP neural network hybrid method for moving objects detection in complex scenes[J].International Journal of Pattern Recognition and Artificial Intelligence,2019,33(2):1950004. [23]ZHU J M,HU L Y.Comparative Analysis of RMB Exchange Rate Forecast Based on ARIMA and BP Neural Network-Take the exchange rate of US dollar to RMB as an example.Journal of Chongqing University of Technology(Natural Science),2019,33(5):207-212. [24]TIAN Z S,CUI Y Q.Attitude measurement fusion algorithm in GPS/SINS based on BP neural-network.Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition),2014,26(4):478-482. |
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