光学精密工程2025，Vol.33Issue(20)：3163-3179,17.DOI:10.37188/OPE.20253320.3163
生物组织偏振成像系统误差校正及甲状腺病理识别
Error correction and thyroid pathology identification of biological tissue polarization imaging system
摘要
Abstract
In order to improve the accuracy and stability of the system in the detection of pathological tis-sue samples,and to explore its application potential in the auxiliary diagnosis of thyroid cancer,a multi-fac-tor cross-module error correction model was proposed to improve the accuracy and stability of the system in the detection of pathological tissue samples.Firstly,the main sources of system errors are analyzed,the error transfer optical path model is established by analytical method and numerical reconstruction method,and a multi-factor cross-module error correction model with 16 calibration parameters is constructed.Sec-ondly,the nonlinear least squares fitting method is used to calibrate 16 parameters.According to the error correction model,the Mueller matrix of the air and blank slices is detected to evaluate the detection accura-cy.Then,using the unstained sections of papillary thyroid carcinoma and nodular goiter as samples,four vector parameters(Δ,P,D,R)were extracted by Mueller matrix polarization decomposition method,and the texture features of each vector parameter image were extracted,and two classification models of random forest and support vector machine were constructed to obtain confusion matrix and ROC curve.Fi-nally,the classification effect was evaluated by calculating Precision,Recall,F1-score,and AUC.The experimental results show that the calibration accuracy is increased by 12%,the calibration stability is in-creased by 21.5%,and the detection accuracy is increased by 59%.The classification effect of random forest was better than that of support vector machine,and the classification effect of Δ parameter was the most significant in random forest classification,with F1-score and AUC reaching 0.96 and AUC,respec-tively.Combined with Mueller matrix polarization decomposition method and texture analysis,the pro-posed multivariate error correction model can effectively distinguish papillary thyroid carcinoma and nodu-lar goiter samples,which provides a new method for early auxiliary diagnosis of cancer and has a good ap-plication prospect.关键词
偏振成像/误差校正/Mueller矩阵矢量参数/纹理特征/随机森林Key words
polarization imaging/error correction/Mueller matrix vector parameters/texture features/random forest分类
数理科学引用本文复制引用
李兵歌,崔岩,鞠宗雨,葛述科,刘金涛..生物组织偏振成像系统误差校正及甲状腺病理识别[J].光学精密工程,2025,33(20):3163-3179,17.基金项目
中央高校基本科研业务(No.DUT23YG206) （No.DUT23YG206）
