An analytical approach for the simulation of realistic low-dose fluoroscopic images

  • Sai Gokul HariharanEmail author
  • Norbert Strobel
  • Christian Kaethner
  • Markus Kowarschik
  • Rebecca Fahrig
  • Nassir Navab
Original Article



The quality of X-ray images plays an important role in computer-assisted interventions. Although learning-based denoising techniques have been shown to be successful in improving the image quality, they often rely on pairs of associated low- and high-dose X-ray images that are usually not possible to acquire at different dose levels in a clinical scenario. Moreover, since data variation is an important requirement for learning-based methods, the use of phantom data alone may not be sufficient. A possibility to address this issue is a realistic simulation of low-dose images from their related high-dose counterparts.


We introduce a novel noise simulation method based on an X-ray image formation model. The method makes use of the system parameters associated with low- and high-dose X-ray image acquisitions, such as system gain and electronic noise, to preserve the image noise characteristics of low-dose images.


We have compared several corresponding regions of the associated real and simulated low-dose images—obtained from two different imaging systems—visually as well as statistically, using a two-sample Kolmogorov–Smirnov test at 5% significance. In addition to being visually similar, the hypothesis that the corresponding regions—from 80 pairs of real and simulated low-dose regions—belonging to the same distribution has been accepted in 81.43% of the cases.


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.


Noise simulation X-ray imaging Simulating low-dose X-ray images 



This work was supported by Siemens Healthineers AG. The concepts and results presented in this paper are based on research and are not commercially available.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© CARS 2019

Authors and Affiliations

  1. 1.Computer Aided Medical ProceduresTechnische Universität MünchenMunichGermany
  2. 2.Siemens Healthineers AG, Advanced TherapiesForchheimGermany
  3. 3.Fakultät für ElektrotechnikHochschule für angewandte Wissenschaften Würzburg-SchweinfurtSchweinfurtGermany
  4. 4.Whiting School of EngineeringJohns Hopkins UniversityBaltimoreUnited States
  5. 5.Pattern Recognition LabFriedrich-Alexander-Universität Erlangen-NürnbergErlangenGermany

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