A new medical imaging toolbox with applications in cancer diagnosis uses technology from CERN (Image: Ander Biguri)
A new medical imaging toolbox, with applications in cancer diagnosis, uses technology from CERN and the same graphic processors found in videogame consoles. Its medical imaging processing can run around 1000 times faster, which means less radiation for the patient.
This collaboration between CERN and the University of Bath, UK, has created an affordable toolbox for fast 3D X-ray image reconstruction for medical applications.
The toolbox is based on Cone Beam Computer Tomography (CBCT), a type of scanning process that takes a series of 2D X-ray pictures and processes them into a 3D image. Ander Biguri, a PhD student at Bath, modified existing algorithms to run on a laptop fitted with a GPU – the same graphic processor found inside standard videogame consoles.
The software should soon be able to incorporate motion compensation to take into account how internal organs move within the patient’s body as they breathe during the scan. The method will be based on a technique developed for CERN’s Proton Synchrotron [link], where proton bunches are imaged as they whizz around the accelerator.
The new software is called the Tomographic Iterative GPU-based Reconstruction (TIGRE) Toolbox, and is available open source. The hope is that the open source approach will create a meeting point for academics and clinicians that will lead to the technology being adopted more widely. Further improvements are already in the pipeline.
CERN’s Knowledge Transfer group played a key role in this project that was coordinated by Dr. Manuchehr Soleimani, director of Engineering Tomography Lab from the University of Bath, and Dr. Steven Hancock from CERN.
Find out more about this open source project and other CERN-related innovation on CERN’s Knowledge Transfer website.
via CERN: Updates for the general public
http://home.cern/about/updates/2016/07/how-can-cern-and-videogames-help-medical-diagnosis
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