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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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Bibliografske podrobnosti
izdano v: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
Jezik:Inglês
Izdano: 2019
Teme:
Online dostop: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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