biological tissues; cancer; computerised tomography; covariance analysis; image classification; image texture; learning (artificial intelligence); lung; medical image processing; wavelet transforms; 3D CT imaging; 3D Riesz features; 3D Riesz-wavelet based covariance descriptors; 3D textured volumes; Riemannian manifold; Riesz-wavelet features; analytical measurement; bag of covariance descriptor paradigm; clustering; covariance-based descriptor formulation; ground-glass opacity; healthy lung; lung nodule tissue; machine learning; manually delineated ground truth; nodule tissue types; radiation oncology specialists; spatial domain; symmetric definite positive matrix; texture classification; tissue density morphology; Biomedical imaging; Computed tomography; Dictionaries; Lungs; Manifolds; Solids; Three-dimensional displays;
机译:基于小波特征描述符和支持向量机的肺结节分类自动化系统
机译:基于协方差的描述符,可实现高效的3D形状匹配,检索和分类
机译:基于纹理特征和分形尺寸变换的CT图像对肺结节分类
机译:基于RIESZ-小波基的协方差描述仪,用于CT中肺结核组织的纹理分类
机译:用于确定肺部CT筛查图像中结节恶性肿瘤的变化描述符
机译:基于小波特征描述和支持向量机的肺结节分类自动系统
机译:使用纹理描述符的CT图像中的肺结节分类