Deep learning based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography.
Max-Heinrich LavesLüder A. KahrsTobias OrtmaierPublished in: CoRR (2018)
Keyphrases
- deep learning
- flow field
- optical coherence tomography
- optical flow estimation
- optical flow
- image sequences
- motion segmentation
- motion analysis
- unsupervised learning
- machine learning
- vector field
- motion field
- mental models
- weakly supervised
- three dimensional
- model selection
- viewpoint
- feature space
- motion estimation
- training set
- cross section
- imaging modalities
- multiscale