Deep supervised learning using self-adaptive auxiliary loss for COVID-19 diagnosis from imbalanced CT images.
Kai HuYingjie HuangWei HuangHui TanZhineng ChenZheng ZhongXuanya LiYuan ZhangXieping GaoPublished in: Neurocomputing (2021)
Keyphrases
- ct images
- supervised learning
- computed tomography
- medical images
- ct scans
- medical imaging
- medical diagnosis
- computer tomography
- lung nodules
- region of interest
- training data
- treatment planning
- pet ct
- semi supervised
- computer aided
- active learning
- machine learning
- mr images
- early diagnosis
- bone segmentation
- image analysis
- automated segmentation
- training set
- medical image processing
- cone beam
- fracture detection