Learning and depicting lobe-based radiomics feature for COPD Severity staging in low-dose CT images.
Meng ZhaoYanan WuYifu LiXiaoyu ZhangShuyue XiaJiaxuan XuRongchang ChenZhenyu LiangShouliang QiPublished in: BMC pulmonary medicine (2024)
The proposed method proved that the novel lobe-based radiomics method can significantly contribute to the refinement of COPD severity staging. By combining radiomic features from each lung lobe, it can obtain a more comprehensive and rich set of features and better capture the CT radiomic features of the lung than simply observing the lung as a whole.
Keyphrases
- contrast enhanced
- low dose
- chronic obstructive pulmonary disease
- computed tomography
- lymph node
- image quality
- deep learning
- lung function
- dual energy
- pet ct
- lymph node metastasis
- magnetic resonance imaging
- machine learning
- positron emission tomography
- magnetic resonance
- high dose
- squamous cell carcinoma
- cystic fibrosis
- convolutional neural network