Fully automated CT to x-ray registration of infected lung regions for COVID-19 patient monitoring

With the sudden outbreak of the novel coronavirus pandemic, patient management protocols have varied across countries. Although imaging is not used for screening due to workflow and resource limitations, studies have shown that Computed tomography(CT) has higher sensitivity than RT-PCR kits in detecting COVID-19. However, since CT requires greater acquisition time and in turn more radiation exposure, X-Ray has been the imaging modality more commonly used. We have developed an analysis protocol to monitor COVID-19 positive patients more efficiently and with greater detail. Our proposed method generates a digitally reconstructed 2D radiographic projection (DRR) from the CT scan, performs Lung segmentation on the coronal CT scan and X-Ray for initial co-registration and finally, fine-tunes the registration using Optimization-based techniques. The difference in the infection area as time progresses can then be monitored on the subsequent X-Ray images throughout the patient’s recovery. The proposed method was evaluated on retrospective data of five COVID-19 positive patients from a single hospital. The patients received a CT within the 1st five days of admission and were followed-up with X-Ray through their recovery process. Our generated DRR’s from the CT showed successful registration to the follow-up X-Rays.