Use of biplane quantitative angiographic imaging with ensemble neural networks to assess reperfusion status during mechanical thrombectomy.
Mohammad Mahdi Shiraz BhurwaniKenneth V. SnyderMohammad WaqasMaxim MokinRyan A. RavaAlexander R. PodgorsakKelsey N. SommerJason M. DaviesElad I. LevyAdnan H. SiddiquiCiprian N. IonitaPublished in: Medical Imaging: Computer-Aided Diagnosis (2021)
Keyphrases
- neural network
- neural network ensemble
- x ray
- pattern recognition
- high resolution
- clinical workflow
- artificial neural networks
- back propagation
- qualitative and quantitative
- genetic algorithm
- image processing
- akaike information criterion
- image analysis
- phase contrast images
- computer vision
- fuzzy logic
- imaging systems
- imaging devices
- clinical practice
- multilayer perceptron
- feed forward
- atomic force microscopy
- multi layer perceptron
- ensemble methods
- medical imaging
- weak learners
- three dimensional
- fault diagnosis
- mechanical design
- radio frequency
- quantitative and qualitative
- neural network model
- random forests
- training process
- fuzzy systems
- ensemble learning