Back to the list
Congress: ECR25
Poster Number: C-28044
Type: Poster: EPOS Radiologist (scientific)
Authorblock: S. Sauranen, T. Mäkelä, T. Kaasalainen, M. Kortesniemi; Helsinki/FI
Disclosures:
Sara Sauranen: Nothing to disclose
Teemu Mäkelä: Nothing to disclose
Touko Kaasalainen: Nothing to disclose
Mika Kortesniemi: Nothing to disclose
Keywords: Artificial Intelligence, Computer applications, Radiation physics, CT, Physics, Technology assessment, Quality assurance
Conclusion

AI noise reduction and the timing of its application during post-processing had a significant impact on the contrast and noise of DECT maps. The DECT maps with AI noise reduction applied to X-ray tube A and B data showed the lowest noise levels. In addition to noise reduction, the contrast levels were slightly changed. An example of the three post-processing versions of the same image is shown in Figure 4.  

Fig 4: The normal and AI noise-reduced versions of a 40 keV virtual monoenergetic image at 4 mGy.
Overall, the AI noise reduction was effective for phantom data. Further study on patient images with qualitative analysis is required to verify and validate the potential clinical benefits of the noise reduction technology.

GALLERY