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ABOUT US
MRI2CT Research Project
Our project aims to revolutionize the workflow control of radiation therapy by developing an innovative solution for generating Synthetic Computed Tomography (sCT) images using hybrid machine learning techniques.
This solution eliminates the need for additional scans, reducing costs and radiation exposure while improving cancer patient outcomes in terms of survival and quality of life. Our research will develop a robust ML pipeline founded on optimal mass transport theory to generate synthetic CT images and estimate electron density information using only MRI images.
Our Vision & Mission
Shaping Our Future Path
Our Vision
To revolutionize radiotherapy treatment planning by integrating synthetic CT images from MRI data, enhancing precision and efficiency in automated treatment planning, to reduce patient burden and elevate care standards.
Our Mission
The project uses deep learning to create synthetic CT images from MRI data for radiotherapy planning. It validates the method against traditional CT, integrates it into software, and conducts clinical trials to assess efficacy and safety.