Paper
15 February 2021 Fully automated CT to x-ray registration of infected lung regions for COVID-19 patient monitoring
Author Affiliations +
Abstract
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.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gautham Nandakumar, Artur Trzesiok, Nikita Thomas, Axel Gedeon Mengara, Akhila Perumalla, Jaewoo Pi, Girish Srinivasan, Rashmi Sama, and Hansuk Kim "Fully automated CT to x-ray registration of infected lung regions for COVID-19 patient monitoring", Proc. SPIE 11601, Medical Imaging 2021: Imaging Informatics for Healthcare, Research, and Applications, 116010Y (15 February 2021); https://doi.org/10.1117/12.2582163
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KEYWORDS
X-rays

Lung

Image segmentation

X-ray computed tomography

X-ray imaging

Artificial intelligence

Computed tomography

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