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Department of Quantitative Biomedicine

The Menze group develops a method to generate accurate synthetic CT images from MRI data

Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network

See Kaushik et al., Phys Med Biol.

In clinical workflow, replacing CT with MR image enhances workflow efficiency and reduces patient radiation. To eliminate CT from the workflow,  the information provided by CT needs to be generated via an MR image. In this work, the Menze group proposes a machine learning method to generate accurate synthetic CT (sCT) from MRI with a quantitative accuracy suitable for RT dose planning application, setting the stage for a broader clinical evaluation of sCT based RT planning on different anatomical regions.