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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Enregistré dans:
Détails bibliographiques
Publié dans:J Med Imaging (Bellingham)
Auteurs principaux: Tang, Yucheng, Gao, Riqiang, Chen, Yunqiang, Gao, Dashan, Savona, Michael R., Abramson, Richard G., Bao, Shunxing, Huo, Yuankai, Landman, Bennett A.
Format: Artigo
Langue:Inglês
Publié: Society of Photo-Optical Instrumentation Engineers 2020
Sujets:
Image Processing
Accès en ligne: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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