Neural Network Training Data Profoundly Impacts Texture-Based Intravascular Image Segmentation.
Akshay GowrishankarLambros S. AthanasiouMax L. OlenderElazer R. EdelmanPublished in: BIBE (2019)
Keyphrases
- neural network
- training data
- image segmentation
- training process
- training patterns
- ultrasound images
- supervised learning
- data sets
- active contours
- markov random field
- neural network model
- artificial neural networks
- training set
- test data
- back propagation
- learning algorithm
- multiscale
- boundary detection
- probabilistic relaxation
- noisy data
- graph cuts
- labeled data
- decision trees
- neural nets
- classification accuracy
- test set
- training algorithm
- deformable models
- self organizing maps
- fuzzy c means
- fuzzy logic
- level set
- medical imaging
- prior knowledge
- training examples
- image processing
- pattern recognition
- gray level
- recurrent neural networks
- feed forward
- texture features
- segmentation algorithm
- expectation maximization
- knn
- computer vision
- genetic algorithm
- segmentation method
- edge detection
- level set method
- contour detection
- method for image segmentation
- neural network is trained