Low-parameter supervised learning models can discriminate pseudoprogression and true progression in non-perfusion-based MRI.
Elisa WarnerJoonsang LeeSanthoshi KrishnanNicholas WangShariq MohammedAshok SrinivasanJayapalli R. BapurajArvind RaoPublished in: EMBC (2023)
Keyphrases
- learning models
- learning algorithm
- machine learning
- semi supervised learning
- magnetic resonance imaging
- loss function
- learning tasks
- semi supervised
- conditional random fields
- medical images
- motion correction
- classification models
- myocardial perfusion
- machine learning algorithms
- mri data
- magnetic resonance images
- supervised learning
- learning problems
- mr imaging
- mr images
- sparse metric learning
- feature selection
- unsupervised learning
- markov random field
- active learning
- prior knowledge
- support vector
- dce mri
- image processing
- genetic algorithm