Cascaded neural network-based CT image processing for aortic root analysis.
Nina KrügerAlexander MeyerLennart TautzMarkus HüllebrandIsaac WamalaMarius PulligMarkus KoflerJörg KempfertSimon SündermannVolkmar FalkAnja HennemuthPublished in: International journal of computer assisted radiology and surgery (2022)
The cascaded neural network approach enabled the assessment of the aortic root with a relatively small training set. The processing time amounts to 30 s per patient, facilitating time-efficient, reproducible measurements. An extended training data set, including different levels of calcification or special cases (e.g., pre-implanted valves), could further improve this method's applicability and robustness.
Keyphrases
- neural network
- aortic valve
- virtual reality
- pulmonary artery
- left ventricular
- transcatheter aortic valve replacement
- aortic valve replacement
- computed tomography
- aortic dissection
- case report
- transcatheter aortic valve implantation
- deep learning
- chronic kidney disease
- aortic stenosis
- electronic health record
- image quality
- dual energy
- machine learning
- coronary artery
- magnetic resonance imaging
- positron emission tomography
- coronary artery disease
- pet ct