Achieving super-resolution X-ray imaging with mobile C-arm devices

C. Bodensteiner*, C. Darolti, A. Schweikard

*Corresponding author for this work
4 Citations (Scopus)


Background: The term super-resolution refers to the process of combining a set of low-resolution images into a high-resolution image using image processing methods. This work is concerned with the reconstruction of high-resolution X-ray images. Specifically, we address the problem of acquiring X-ray images from multiple, very close view points. Methods: We propose to use a novel experimental robotic C-arm device to create high-resolution X-ray images. For this purpose, we suggest different strategies for acquiring multiple low-resolution images, and we provide the steps to achieve acquisition-error compensation. Compared to visible light images, X-ray images have the particularity that parallax effects render super-resolution very difficult. Using the acquired multi-frame data, we evaluate recent well-known super-resolution reconstruction algorithms. The same algorithms are evaluated based on synthetic 3D phantom data and real X-ray images. Results: In experiments with both synthetic and real projection data, we successfully reconstruct up to four times higher-resolution images. These images reveal structures and details which are not perceivable in the low-resolution images. Conclusions: The advantage of super-resolution techniques for X-ray is the potential reduction of radiation dose for patients and medical personnel. Potential medical applications include the diagnosis of earlystage osteoporosis and the detection of very small calcifications.

Original languageEnglish
JournalInternational Journal of Medical Robotics and Computer Assisted Surgery
Issue number3
Pages (from-to)243-256
Number of pages14
Publication statusPublished - 01.09.2009


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