Automatic segmentation and analysis of the main pulmonary artery on standard post-contrast CT studies using iterative erosion and dilation.
Daniel Aaron MosesClaude SammutTatjana ZrimecPublished in: International journal of computer assisted radiology and surgery (2015)
Our algorithm is a robust accurate automated method for obtaining measurements of the MPA. This allows a more standardized method for determining length, and mid- cross-sectional area/perimeter and therefore allows more accurate comparison of MPA measurements.
Keyphrases
- pulmonary artery
- deep learning
- coronary artery
- machine learning
- pulmonary hypertension
- cross sectional
- pulmonary arterial hypertension
- image quality
- convolutional neural network
- dual energy
- high resolution
- contrast enhanced
- computed tomography
- magnetic resonance
- magnetic resonance imaging
- neural network
- case control
- positron emission tomography