Deep learning-based calculation of patient size and attenuation surrogates from localizer image: toward personalized chest ct protocol optimization

HIGHLIGHTS

• who: Yazdan Salimi from the University of Southern Denmark have published the article: Deep Learning-based calculation of patient size and attenuation surrogates from localizer Image: Toward personalized chest CT protocol optimization, in the Journal: (JOURNAL) of 27/04/2022
• what: This study proposed unified methu00ad odology to measure patient shape and attenuation parameters from 2D anterior-posterior localizer using deep learning algorithms without the need for labor-intensive vendor-specific calibration procedures. To evaluate the effect of TH and patient misregistration in the AP direction on the accuracy of the model , the authors excluded . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.