Deep-learning-based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography.
Max-Heinrich LavesSontje IhlerLüder A. KahrsTobias OrtmaierPublished in: Medical Imaging: Image-Guided Procedures (2019)
Keyphrases
- deep learning
- flow field
- optical coherence tomography
- optical flow estimation
- optical flow
- image sequences
- unsupervised learning
- motion analysis
- motion segmentation
- weakly supervised
- vector field
- motion field
- retinal images
- imaging modalities
- machine learning
- mental models
- motion model
- viewpoint
- missing data
- model selection
- principal component analysis
- motion estimation
- active learning
- image analysis
- multiscale
- image processing