Machine Learning Based on Computed Tomography Pulmonary Angiography in Evaluating Pulmonary Artery Pressure in Patients with Pulmonary Hypertension.
Nan ZhangXin ZhaoJie LiLiqun HuangHaotian LiHaiyu FengMarcos A GarciaYunshan CaoZhonghua SunSenchun ChaiPublished in: Journal of clinical medicine (2023)
The proposed machine learning framework on CTPA enables accurate segmentation of pulmonary artery and heart and automatic assessment of the PAP parameters and has the ability to accurately distinguish different PH patients with mPAP and sPAP. Results of this study may provide additional risk stratification indicators in the future with non-invasive CTPA data.
Keyphrases
- pulmonary artery
- pulmonary hypertension
- machine learning
- computed tomography
- deep learning
- pulmonary arterial hypertension
- big data
- coronary artery
- artificial intelligence
- positron emission tomography
- optical coherence tomography
- magnetic resonance imaging
- convolutional neural network
- electronic health record
- current status
- high resolution
- contrast enhanced
- atrial fibrillation