Our official English website, www.x-mol.net, welcomes your
feedback! (Note: you will need to create a separate account there.)
An effective deep network for automatic segmentation of complex lung tumors in CT images
Medical Physics ( IF 3.2 ) Pub Date : 2021-07-05 , DOI: 10.1002/mp.15074 Bing Wang 1 , Kang Chen 1 , Xuedong Tian 2 , Ying Yang 3 , Xin Zhang 4
Medical Physics ( IF 3.2 ) Pub Date : 2021-07-05 , DOI: 10.1002/mp.15074 Bing Wang 1 , Kang Chen 1 , Xuedong Tian 2 , Ying Yang 3 , Xin Zhang 4
Affiliation
Accurate segmentation of complex tumors in lung computed tomography (CT) images is essential to improve the effectiveness and safety of lung cancer treatment. However, the characteristics of heterogeneity, blurred boundaries, and large-area adhesion to tissues with similar gray-scale features always make the segmentation of complex tumors difficult.
中文翻译:
用于自动分割 CT 图像中复杂肺部肿瘤的有效深度网络
准确分割肺计算机断层扫描 (CT) 图像中的复杂肿瘤对于提高肺癌治疗的有效性和安全性至关重要。然而,异质性、边界模糊、与具有相似灰度特征的组织大面积粘附等特点,总是使复杂肿瘤的分割变得困难。
更新日期:2021-07-05
中文翻译:
用于自动分割 CT 图像中复杂肺部肿瘤的有效深度网络
准确分割肺计算机断层扫描 (CT) 图像中的复杂肿瘤对于提高肺癌治疗的有效性和安全性至关重要。然而,异质性、边界模糊、与具有相似灰度特征的组织大面积粘附等特点,总是使复杂肿瘤的分割变得困难。