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Application of Unenhanced Computed Tomography texture analysis to Differentiate Pancreatic Adenosquamous Carcinoma from Pancreatic Ductal Adenocarcinoma

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Current Medical Science 2022年第1期42卷 217-225页

作者： Shuai REN Hui-juan TANG Rui ZHAO Shao-feng DUAN Rong CHEN Zhong-qiu WANG Department of Radiology Jiangsu Province Hospital of Chinese MedicineAffiliated Hospital of Nanjing University of Chinese MedicineNanjing 210029China Department of Diagnostic Radiology and Nuclear Medicine School of MedicineUniversity of MarylandBaltimoreMD 21201USA Department of Oncology Jiangsu Province Hospital of Chinese MedicineAffiliated Hospital of Nanjing University of Chinese MedicineNanjing 210029China Department of Clinical and Molecular Sciences Marche Polytechnic UniversityAncona 60126Italy GE Healthcare Shanghai 201203China

Objective:The objective of this study was to investigate the application of unenhanced computed tomography(CT)texture analysis in differentiating pancreatic adenosquamous carcinoma(PASC)from pancreatic ductal adenocarcinoma(PDAC).Methods:Preoperative CT images of 112 patients(31 with PASC,81 with PDAC)were retrospectively reviewed.A total of 396 texture parameters were extracted from analysisKit software for further texture analysis.texture features were selected for the differentiation of PASC and PDAC by the Mann-Whitney U test,univariate logistic regression analysis,and the minimum redundancy maximum relevance algorithm.Furthermore,receiver operating characteristic(ROC)curve analysis was performed to evaluate the diagnostic performance of the texture feature-based model by the random forest(RF)method.Finally,the robustness and reproducibility of the predictive model were assessed by the 10-times leave-group-out cross-validation(LGOCV)method.

关键词： platelet doubling computed tomography pancreatic neoplasms adenocarcinoma adenosquamous carcinoma texture analysis

Quantitative dual-energy computed tomography texture analysis predicts the response of primary small hepatocellular carcinoma to radiofrequency ablation

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Hepatobiliary & Pancreatic Diseases International 2022年第6期21卷 569-576页

作者： Jin-Ping Li Sheng Zhao Hui-Jie Jiang Hao Jiang Lin-Han Zhang Zhong-Xing Shi Ting-Ting Fan Song Wang Department of Radiology the Second Affiliated Hospital of Harbin Medical UniversityHarbin 150086China Department of Nuclear Medicine the First Affiliated Hospital of Harbin Medical UniversityHarbin 150086China Department of Radiology Longhua HospitalShanghai University of Traditional Chinese MedicineShanghai 200032China

Background:Radiofrequency ablation(RFA)is one of the effective therapeutic modalities in patients with hepatocellular carcinoma(HCC).However,there is no proper method to evaluate the HCC response to RFA.This study aimed to establish and validate a clinical prediction model based on dual-energy com-puted tomography(DECT)quantitative-imaging parameters,clinical variables,and CT texture parameters.Methods:We enrolled 63 patients with small HCC.Two to four weeks after RFA,we performed DECT scanning to obtain DECT-quantitative parameters and to record the patients’clinical baseline variables.DECT images were manually segmented,and 56 CT texture features were extracted.We used LASSO al-gorithm for feature selection and data dimensionality reduction;logistic regression analysis was used to build a clinical model with clinical variables and DECT-quantitative parameters;we then added texture features to build a clinical-texture model based on clinical model.Results:A total of six optimal CT texture analysis(CTTA)features were selected,which were statis-tically different between patients with or without tumor progression(Ptexture models showed that ALBI(OR=2.40,95%CI:1.19-5.68,P=0.024),λAP(40-100 keV)(OR=1.43,95%CI:1.10-2.07,P=0.019),and CTTA-score(OR=2.98,95%CI:1.68-6.66,P=0.001)were independent risk factors for tumor progression.The clinical model,clinical-texture model,and CTTA-score all performed well in predicting tumor progression within 12 months after RFA(AUC=0.917,0.962,and 0.906,respectively),and the C-indexes of the clinical and clinical-texture models were 0.917 and 0.957,respectively.Conclusions:DECT-quantitative parameters,CTTA,and clinical variables were help

关键词： Hepatocellular carcinoma Dual-energy Radiofrequency ablation Tumor response texture analysis

Hurricane eye morphology extraction from SAR images by texture analysis

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Frontiers of Earth Science 2022年第1期16卷 190-205页

作者： Weicheng NI Ad STOFFELEN Kaijun REN Royal Netherlands Meteorological Institute De Bilt 3731GAThe Netherlands College of Meteorology and Oceanography National University of Defense TechnologyChangsha 410073China

Tropical hurricanes are among the most devastating hazards on Earth.Knowledge about its intense inner-core structure and dynamics will improve hurricane forecasts and advisories.The precise morphological parameters extracted from high-resolution spaceborne Synthetic Aperture Radar(SAR)images,can play an essential role in further exploring and monitoring hurricane dynamics,especially when hurricanes undergo amplification,shearing,eyewall replacements and so forth.Moreover,these parameters can help to build guidelines for wind calibration of the more abundant,but lower resolution scatterometer wind data,thus better linking scatterometer wind fields to hurricane categories.In this paper,we develop a new method for automatically extracting the hurricane eyes from C-band SAR data by constructing Gray Level-Gradient Co-occurrence Matrices(GLGCMs).The hurricane eyewall is determined with a two-dimensional vector,generated by maximizing the class entropy of the hurricane eye region in GLGCM.The results indicate that when the hurricane is weak,or the eyewall is not closed,the hurricane eye extracted with this automatic method still agrees with what is observed visually,and it preserves the texture characteristics of the original image.As compared to Du’s wavelet analysis method and other morphological analysis methods,the approach developed here has reduced artefacts due to factors like hurricane size and has lower programming complexity.In summary,the proposed method provides a new and elegant choice for hurricane eye morphology extraction.

关键词： hurricane eyewall morphological parameter texture analysis Gray Level-Gradient Co-occurrence Matrix Two-dimensional Entropy Maximization

The utility of two-dimensional shear wave elastography and texture analysis for monitoring liver fibrosis in rat model

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Hepatobiliary & Pancreatic Diseases International 2021年第1期20卷 46-52页

作者： Li-Hong Gu Guang-Xiang Gu Ping Wan Feng-Hua Li Qiang Xia Department of Liver Surgery Renji HospitalSchool of MedicineShanghai Jiaotong UniversityShanghai 200127China Department of Ultrasound Renji HospitalSchool of MedicineShanghai Jiaotong UniversityShanghai 200127China

Background:Liver fibrosis is a common pathological change caused by a variety of etiologies.Early diagnosis and timely treatment can reverse or delay disease progression and improve the prognosis.This study aimed to assess the potential utility of two-dimensional shear wave elastography and texture analysis in dynamic monitoring of the progression of liver fibrosis in rat model.Methods:Twenty rats were divided into control group(n=4)and experimental groups(n=4 per group)with carbon tetrachloride administration for 2,3,4,and 6 weeks.The liver stiffness measurement was performed by two-dimensional shear wave elastography,while the optimal texture analysis subsets to distinguish fibrosis stage were generated by MaZda.The results of elastography and texture analysis were validated through comparing with histopathology.Results:Liver stiffness measurement was 6.09±0.31 kPa in the control group and 7.10±0.41 kPa,7.80±0.93 kPa,8.64±0.93 kPa,9.91±1.13 kPa in the carbon tetrachloride induced groups for 2,3,4,6 weeks,respectively(Ptexture analysis,histogram and co-occurrence matrix had the most frequency texture parameters in staging liver fibrosis.Receiver operating characteristic curve of liver elasticity showed that the sensitivity and specificity were 95.0%and 92.5%to discriminate liver fibrosis and non-fibrosis,respectively.In texture analysis,five optimal parameters were selected to classify liver fibrosis and non-fibrosis.Conclusions:Two-dimensional shear wave elastography showed potential applications for noninvasive monitoring of the progression of hepatic fibrosis,even in mild fibrosis.texture analysis can further extract and quantify the texture features in ultrasonic image,which was a supplementary to further visual information and acquired high diagnostic accuracy for severe fibrosis.

关键词： Shear wave elastography Ultrasound texture analysis Fibrosis Rat

CT texture analysis: A Potential Biomarker for Evaluating KRAS Mutational Status in Colorectal Cancer

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Chinese Medical Sciences Journal 2020年第4期35卷 306-314页

作者： Jian Cao Guorong Wang Zhiwei Wang Zhengyu Jin Department of Radiology Peking Union Medical College HospitalChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China

Objective texture analysis is deemed to reflect intratumor heterogeneity invisible to the naked eyes.The aim of this study was to evaluate the feasibility of assessing the KRAS mutational status in colorectal cancer(CRC)patients using CT texture analysis.Methods This retrospective study included 92 patients who had histopathologically confirmed CRC and underwent preoperative contrast-enhanced CT examinations.The patients were assigned into a training cohort(n=51)and a validation cohort(n=41).We placed the region of interest in the tumour regions on the selected axial images using software of lexRad to extract a series of quantitative parameters based on the spatial scaling factors(SSFs),including mean,standard deviation(SD),entropy,mean of positive pixels(MPP),skewness,and kurtosis.The texture parameters and clinical characteristics(age,gender,tumour location,histopathology;tumour size,1 N,M stages)were compared between the mutated and wild-type KRAS patient groups in training cohort and validation cohort.Before building the multiple feature classifier,we calculated the correlations of the features using Pearsons correlation coefficient,and if any two features were significantly correlated,the one with lower AUC was removed.Ultimately,only the most discriminative isolated features were combined to train a supporting vector machine(SVM)classifier.The receiver operating characteristic(ROC)curve was processed for evaluating the diagnostic efficiency of texture parameters in differentiating CRC patients with mutated KRAS from those with wild-type KRAS.Results None of the clinical characteristics were significant different between CRC patients with wild-type KRAS and mutated KRAS in both cohorts.For predicting the expression of mutated KRAS in CRC patients,the perfect model which combined skewness on SSF 5 by unenhanced CT,entropy on SSF 2,skewness and kurtosis on SSF 0,and kurtosis and mean on SSF 3 by enhanced CT,showed a desirable AUC of 0.951(95%CI:0.895-1,P<0.001),with a sensitivity of 88.9%and a specificity of 9

关键词： biological markers colorectal neoplasms texture analysis computed tomography

Diagnostic performance of texture analysis in the differential diagnosis of perianal fistulising Crohn’s disease and glandular anal fistula

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World Journal of Gastrointestinal Surgery 2023年第5期15卷 882-891页

作者： Xin Zhu Dan-Dan Ye Jian-Hua Wang Jing Li Shao-Wei Liu Department of Radiology Affiliated Hospital of Nanjing University of Chinese MedicineNanjing 210029Jiangsu ProvinceChina Department of Radiology Quanzhou Orthopedic-Traumatological HospitalQuanzhou 362000Fujian ProvinceChina

BACKGROUND Perianal fistulising Crohn's disease(PFCD)and glandular anal fistula have many similarities on conventional magnetic resonance imaging.However,many patients with PFCD show concomitant active proctitis,but only few patients with glandular anal fistula have active proctitis.AIM To explore the value of differential diagnosis of PFCD and glandular anal fistula by comparing the textural feature parameters of the rectum and anal canal in fat suppression T2-weighted imaging(FS-T2WI).METHODS Patients with rectal water sac implantation were screened from the first part of this study(48 patients with PFCD and 22 patients with glandular anal fistula).Open-source software ITK-SNAP(Version 3.6.0,http://***/)was used to delineate the region of interest(ROI)of the entire rectum and anal canal wall on every axial section,and then the ROIs were input in the analysis Kit software(version V3.0.0.R,GE Healthcare)to calculate the textural feature parameters.Textural feature parameter differences of the rectum and anal canal wall between the PFCD group vs the glandular anal fistula group were analyzed using Mann-Whitney U test.The redundant textural parameters were screened by bivariate Spearman correlation analysis,and binary logistic regression analysis was used to establish the model of textural feature parameters.Finally,diagnostic accuracy was assessed by receiver operating characteristic-area under the curve(AUC)analysis.RESULTS In all,385 textural parameters were obtained,including 37 parameters with statistically significant differences between the PFCD and glandular anal fistula groups.Then,16 texture feature parameters remained after bivariate Spearman correlation analysis,including one histogram parameter(Histogram energy);four grey level co-occurrence matrix(GLCM)parameters(GLCM energy_all direction_offset1_SD,GLCM entropy_all direction_offset4_SD,GLCM entropy_all direction_offset7_SD,and Haralick correlation_all direction_offset7_SD);four texture parameters(Correlation_all direction_offset1_SD,cluster prominenc

关键词： Anal fistula Crohn’s diseases Magnetic resonance imaging texture analysis Differential diagnosis

Tea Leaves Classification Based on texture analysis

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Tea Leaves Classification Based on Texture Analysis

The Clinical Value of Ultrasound Image texture analysis in the Diagnosis of Uterine Adhesions

2015年中国智能自动化学术会议

作者： Zhe Tang Fang Qi Yi Zhou Fangfang Pan Jianyong Zhou School of Information Science and Engineering Central South University

An SVM with texture analysis-based feature extraction classification method is presented for identification of fresh tea leaves in this paper. This method is proved to be very efficient and effective in the identification of fresh tea leaves through real experiments. First, the texture characteristic parameters of tea leave images are obtained by texture feature extraction. After that, different categories of fresh tea leaves are identified through SVM training. These texture parameters for texture classification include energy, correlation, and contrast obtained from graylevel co-occurrence matrix(GLCM). Experimental results show that the use of SVM for classification of tea leaves can achieve very good results, and the successful classification rate can be as high as 83 %.

关键词： texture analysis GLCM SVM Tea leaves classification

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Open Journal of Obstetrics and Gynecology 2024年第2期14卷 312-320页

作者： Meng Li Chanyu Zhang Department of Gynaecology and Obstetrics The Second Affiliated Hospital of Chongqing Medical University Chongqing China

Purpose: This review examines the diagnostic value of transvaginal 3D ultrasound image texture analysis for the diagnosis of uterine adhesions. Materials and Methods: The total clinical data of 53 patients with uterine adhesions diagnosed by hysteroscopy and the imaging data of transvaginal three-dimensional ultrasound from the Second Affiliated Hospital of Chongqing Medical University from June 2022 to August 2023 were retrospectively analysed. Based on hysteroscopic surgical records, patients were divided into two independent groups: normal endometrium and uterine adhesion sites. The samples were divided into a training set and a test set, and the transvaginal 3D ultrasound was used to outline the region of interest (ROI) and extract texture features for normal endometrium and uterine adhesions based on hysteroscopic surgical recordings, the training set data were feature screened and modelled using lasso regression and cross-validation, and the diagnostic efficacy of the model was assessed by applying the subjects’ operating characteristic (ROC) curves. Results: For each group, 290 texture feature parameters were extracted and three higher values were screened out, and the area under the curve of the constructed ultrasonographic scoring model was 0.658 and 0.720 in the training and test sets, respectively. Conclusion Relative clinical value of transvaginal three-dimensional ultrasound image texture analysis for the diagnosis of uterine adhesions.

关键词： Transvaginal 3D Ultrasound Intrauterine Adhesion texture analysis

Gabor Filter Optimization Design for Iris texture analysis

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Journal of Bionic Engineering 2004年第1期1卷 72-78页

作者： Tao Xu 1, Xing Ming 2, Xiaoguang Yang 3 1.College of Mechanical Science and Engineering, Jilin University, Changchun 130022, P.R.China 2.College of Computer Science and Technology, Jilin University, Changchun 130022, P.R.China 3.Dept of Mathematics and Physics, Dalian Maritime University, Dalian 116026,P.R.China College of Mechanical Science and Engineering Jilin University Changchun 130022 P.R. China College of Computer Science and Technology Jilin University Changchun 130022 P.R. China Dept of Mathematics and Physics Dalian Maritime University Dalian 116026P. R. China

This paper deals with an optimization design method for the Gabor filters based on the analysis of an iris texture model. By means of analyzing the properties of an iris texture image, the energy distribution regularity of the iris texture image measured by the average power spectrum density is exploited, and the theoretical ranges of the efficient valued frequency and orientation parameters can also be deduced. The analysis shows that the energy distribution of the iris texture is generally centralized around lower frequencies in the spatial frequency domain. Accordingly, an iterative algorithm is designed to optimize the Gabor parameter field. The experimental results indicate the validity of the theory and efficiency of the algorithm.

关键词： iris recognition texture analysis receptive profile Gabor filter parameter field optimization method