medigan: A Python Library of Pretrained Generative Models for Enriched Data Access in Medical Imaging.
Richard OsualaGrzegorz SkorupkoNoussair LazrakLidia GarruchoEloy GarcíaSmriti JoshiSocayna JouideMichael RutherfordFred PriorKaisar KushibarOliver DíazKarim LekadirPublished in: CoRR (2022)
Keyphrases
- data access
- medical imaging
- generative model
- data management
- medical images
- x ray
- image registration
- probabilistic model
- image segmentation
- discriminative learning
- image analysis
- image processing
- database applications
- discriminative models
- open source
- em algorithm
- prior knowledge
- programming language
- data objects
- hierarchical hidden markov models
- computer vision
- expectation maximization
- generative and discriminative models
- conditional random fields
- visual basic
- semi supervised
- remote sensing
- knowledge discovery
- database systems
- graphical models
- database management systems
- digital libraries
- multiscale
- decision making
- information retrieval