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Towards Effcient Label Fusion by Pre-Alignment of Training Data

Label fusion is a multi-atlas segmentation approach that explicitly maintains and exploits the entire training dataset, rather than a parametric summary of it. Recent empirical evidence suggests that label fusion can achieve significantly better segmentation accuracy over classical parametric atlas...

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Hlavní autoři: Depa, Michal, Holmvang, Godtfred, Schmidt, Ehud J., Golland, Polina, Sabuncu, Mert R.
Médium: Artigo
Jazyk:Inglês
Vydáno: 2011
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC3958940/
https://ncbi.nlm.nih.gov/pubmed/24660167
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