Improving Splenomegaly Segmentation by Learning from Heterogeneous Multi-Source Labels

Splenomegaly segmentation on computed tomography (CT) abdomen anatomical scans is essential for identifying spleen biomarkers and has applications for quantitative assessment in patients with liver and spleen disease. Deep convolutional neural network automated segmentation has shown promising perfo...

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Bibliografiske detaljer
Udgivet i:Proc SPIE Int Soc Opt Eng
Main Authors: Tang, Yucheng, Huo, Yuankai, Xiong, Yunxi, Moon, Hyeonsoo, Assad, Albert, Moyo, Tamara K., Savona, Michael R., Abramson, Richard, Landman, Bennett A.
Format: Artigo
Sprog:Inglês
Udgivet: 2019
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Article
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6874226/
https://ncbi.nlm.nih.gov/pubmed/31762532
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/12.2512842
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