Automatic Segmentation of Type A Aortic Dissection on Computed Tomography Images Using Deep Learning Approach.
Xiaoya GuoTianshu LiuYi YangJianxin DaiLiang WangDalin TangHao-Liang SunPublished in: Diagnostics (Basel, Switzerland) (2024)
The nnU-Net architectures may serve as a basis for automatic segmentation and quantification of TAAD, which could aid in rapid diagnosis, surgical planning, and subsequent biomechanical simulation of the aorta.
Keyphrases
- deep learning
- aortic dissection
- convolutional neural network
- computed tomography
- artificial intelligence
- machine learning
- positron emission tomography
- magnetic resonance imaging
- pulmonary artery
- aortic valve
- loop mediated isothermal amplification
- contrast enhanced
- magnetic resonance
- pulmonary hypertension
- finite element analysis
- coronary artery
- virtual reality
- optical coherence tomography
- quantum dots