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...

Полное описание

Сохранить в:
Библиографические подробности
Опубликовано в: :J Med Imaging (Bellingham)
Главные авторы: Tang, Yucheng, Gao, Riqiang, Chen, Yunqiang, Gao, Dashan, Savona, Michael R., Abramson, Richard G., Bao, Shunxing, Huo, Yuankai, Landman, Bennett A.
Формат: Artigo
Язык:Inglês
Опубликовано: Society of Photo-Optical Instrumentation Engineers 2020
Предметы:
Image Processing
Online-ссылка: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
Метки: Добавить метку
Нет меток, Требуется 1-ая метка записи!

Схожие документы