Graduate Student Makes Progress in Medical Imaging
Graduate student Shobhit Sharma and his advisors Profs. Ehsan Samei and Anuj Kapadia report that accurate individualized estimates of organ doses in computed tomography (CT) can now be performed within clinically acceptable computation times. They utilized an automatic image-segmentation method to create custom anatomical models from patients’ CT data along with a parallelized Monte Carlo simulation of photon transport to compute the radiation burden imposed by a CT scan in less than half a minute – hundreds of times faster than non-parallelized Monte Carlo methods. The availability of such a tool will enable access to patients’ personalized dose histories and would help clinicians make cost–benefit decisions about any subsequent CT imaging procedures that deliver additional radiation dose. More details about their work can be found here.
Photo: Sample slices from a CT image dataset (top row), along with the corresponding masks for the automatically segmented organs used to generate patient-specific anatomy models. (Courtesy: S Sharmaet al Phys. Med. Biol. 10.1088/1361-6560/ab467f)