Random effects during training: Implications for deep learning-based medical image segmentation.
Julius ÅkessonJohannes TögerEinar HeibergPublished in: Comput. Biol. Medicine (2024)
Keyphrases
- deep learning
- medical image segmentation
- random effects
- medical images
- hidden markov models
- unsupervised learning
- medical image analysis
- curve evolution
- machine learning
- level set method
- statistical shape model
- weakly supervised
- image segmentation
- deformable models
- mental models
- supervised learning
- training set
- pattern recognition
- linear model
- d objects
- decision trees
- learning algorithm