Low-Dose CT Image Synthesis for Domain Adaptation Imaging Using a Generative Adversarial Network With Noise Encoding Transfer Learning.
Ming LiJiping WangYang ChenYufei TangZhongyi WuYujin QiHaochuan JiangJian ZhengBenjamin M. W. TsuiPublished in: IEEE Trans. Medical Imaging (2023)
Keyphrases
- low dose
- domain adaptation
- transfer learning
- image synthesis
- x ray
- computed tomography
- target domain
- ct scans
- imaging modalities
- cross domain
- source domain
- computer tomography
- manifold alignment
- labeled data
- ct images
- lung nodules
- learning tasks
- medical imaging
- semi supervised learning
- transfer knowledge
- medical images
- reinforcement learning
- knowledge transfer
- machine learning
- active learning
- collaborative filtering
- image reconstruction
- clinical applications
- text classification
- learning algorithm
- semi supervised
- multiple sources
- sentiment classification
- unlabeled data
- text categorization
- three dimensional
- intraoperative
- unsupervised learning
- multi view
- test data
- machine learning algorithms
- training data
- image processing
- data mining