An analytical approach for the simulation of realistic low-dose fluoroscopic images.
Sai Gokul HariharanNorbert StrobelChristian KaethnerMarkus KowarschikRebecca FahrigNassir NavabPublished in: International journal of computer assisted radiology and surgery (2019)
The results suggest that the simulated low-dose images obtained using the proposed method are almost indistinguishable from real low-dose images. Since extensive calibration procedures required in previous methods can be avoided using the proposed approach, it allows an easy adaptation to different X-ray imaging systems. This in turn leads to an increased diversity of the training data for potential learning-based methods.
Keyphrases
- low dose
- deep learning
- convolutional neural network
- high dose
- optical coherence tomography
- high resolution
- virtual reality
- electronic health record
- artificial intelligence
- fluorescent probe
- computed tomography
- big data
- sensitive detection
- magnetic resonance
- living cells
- liquid chromatography
- climate change
- low cost
- single molecule