医疗卫生装备2017，Vol.38Issue(6)：12-16,5.DOI:10.7687/j.issn1003-8868.2017.06.012
基于高阶导数变换的纹理特征在膀胱肿瘤中的应用研究
Texture features based on high-order derivative maps for differentiation of bladder cancer
摘要
Abstract
Objective To determine the three-dimensional (3D) texture features extracted from intensity and high-order derivative maps that could reflect textural differences between bladder tumors and wall tissues,in order to achieve bladder cancer and wall tissue identification.Methods A total of 62 cancerous and 62 wall volumes of interest (VOI) were extracted from T2-weighted MRI datasets of 62 patients with pathologically confirmed bladder cancer.To reflect heterogeneous distribution of tumor tissues,3D high-order derivative maps (the gradient and curvature maps) were calculated from each VOI.Then 3D Haralick features based on intensity and high-order derivative maps and Tamura features based on intensity maps were extracted from each VOI.Statistical analysis was proposed to first select the features with significant differences and then obtain a more predictive and compact feature subset to verify its differentiation performance.Results From each VOI,a total of 58 texture features were derived.Among them,37 features showed significant inter-class differences (P≤ 0.01).Conclusion The results suggest that 3D texture features deriving from intensity and high-order derivative maps can reflect heterogeneous distribution of cancerous tissues.关键词
膀胱肿瘤/磁共振/三维纹理特征/高阶偏导变换/纹理特征提取Key words
bladder cancer/MRI/three-dimensional texture feature/high-order partial derivative transformation/texture feature extraction分类
医药卫生引用本文复制引用
徐肖攀,曹学瀚,袁娟丽,卢虹冰,曹波伟..基于高阶导数变换的纹理特征在膀胱肿瘤中的应用研究[J].医疗卫生装备,2017,38(6):12-16,5.基金项目
国家自然科学基金资助项目(81230035) （81230035）
陕西省社会发展科技攻关项目(2016SF302) （2016SF302）
