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Achieving super‐resolution X‐ray imaging with mobile C‐arm devices
Author(s) -
Bodensteiner C.,
Darolti C.,
Schweikard A.
Publication year - 2009
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.255
Subject(s) - computer science , computer vision , artificial intelligence , projection (relational algebra) , resolution (logic) , image resolution , data set , imaging phantom , medical imaging , nuclear medicine , algorithm , medicine
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 early‐stage osteoporosis and the detection of very small calcifications. Copyright © 2009 John Wiley & Sons, Ltd.