Learning from dispersed manual annotations with an optimized data weighting policy

Purpose: Deep learning methods have become essential tools for quantitative interpretation of medical imaging data, but training these approaches is highly sensitive to biases and class imbalance in the available data. There is an opportunity to increase the available training data by combining acro...

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Detalhes bibliográficos
Publicado no:J Med Imaging (Bellingham)
Main Authors: Tang, Yucheng, Gao, Riqiang, Chen, Yunqiang, Gao, Dashan, Savona, Michael R., Abramson, Richard G., Bao, Shunxing, Huo, Yuankai, Landman, Bennett A.
Formato: Artigo
Idioma:Inglês
Publicado em: Society of Photo-Optical Instrumentation Engineers 2020
Assuntos:
Image Processing
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7394463/
https://ncbi.nlm.nih.gov/pubmed/32775501
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.7.4.044002
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