AutoEDES: a model-based Bayesian framework for automatic end-diastolic and end-systolic frame selection in angiographic image sequence.
Wei QuSukhveer SinghMike KellerPublished in: Medical Imaging: Computer-Aided Diagnosis (2008)
Keyphrases
- bayesian framework
- image sequences
- prior knowledge
- three dimensional
- generative model
- fully automatic
- hyperparameters
- bayesian model
- spatio temporal
- image frames
- maximum a posteriori
- posterior probability
- gaussian process
- bayesian formulation
- learning algorithm
- bayesian methods
- posterior distribution
- expectation maximization
- video sequences
- computer vision