Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea;
Department of Industrial Engineering, Seoul National University College of Engineering, Seoul, Republic o;
linear binning; non-linear binning; unsupervised learning; diffuse inflltrative lung disease; texture analysis; clustering;
机译:基于HRCT纹理特征的阻塞性肺疾病之间自动区分系统的最佳分类和ROI大小
机译:基于HRCT纹理特征的阻塞性肺疾病之间自动区分系统的最佳分类和ROI大小
机译:HRCT鉴别梗阻性肺疾病自动分类系统的开发
机译:各种衬砌方法和ROI大小对自动分类系统的准确性,在HRCT纹理特征基础上弥漫性血迹肺病差异
机译:基于HRCT图像与间质肺病的纹理和深度特征的自动肺分割
机译:HRCT鉴别梗阻性肺疾病自动分类系统的开发