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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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書目詳細資料
發表在: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.
格式: Artigo
語言:Inglês
出版: 2019
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在線閱讀: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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