Registration Error and Intensity Similarity Based Label Fusion for Segmentation
Sign Up to like & getrecommendations! Published in 2019 at "IRBM"
DOI: 10.1016/j.irbm.2019.02.001
Abstract: Abstract Background Label fusion is a core step of Multi-Atlas Segmentation (MAS), which has a decisive effect on segmentation results. Although existed strategies using image intensity or image shape to fuse labels have got acceptable… read more here.
Keywords: intensity; fusion; registration error; segmentation ... See more keywords
High-Order Feature Learning for Multi-Atlas Based Label Fusion: Application to Brain Segmentation With MRI
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2019.2952079
Abstract: Multi-atlas based segmentation methods have shown their effectiveness in brain regions-of-interesting (ROIs) segmentation, by propagating labels from multiple atlases to a target image based on the similarity between patches in the target image and multiple… read more here.
Keywords: label fusion; high order; image; brain ... See more keywords