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Heterogeneous Stitching of X-ray Images According to Homographic Evaluation

Heterogeneous Stitching of X-ray Images According to Homographic Evaluation
Ha, Ho-GunJung, KyunghwaLee, SeongpungLee, HyunKiHong, Jaesung
Issued Date
Journal of Digital Imaging
Author Keywords
Image stitchingPanoramic imagingC-armFluoroscopy
Feature extractionRobotic armsSurgeryBone fragmentsConventional methodsFeature detectionFracture reductionFractured bonesIntra-operative imagingOrthopedic surgeryOverlap regionImage processing
The C-arm X-ray system is a common intraoperative imaging modality used to observe the state of a fractured bone in orthopedic surgery. Using C-arm, the bone fragments are aligned during surgery, and their lengths and angles with respect to the entire bone are measured to verify the fracture reduction. Since the field-of-view of the C-arm is too narrow to visualize the entire bone, a panoramic X-ray image is utilized to enlarge it by stitching multiple images. To achieve X-ray image stitching with feature detection, the extraction of accurate and densely matched features within the overlap region between images is imperative. However, since the features are highly affected by the properties and sizes of the overlap regions in consecutive X-ray images, the accuracy and density of matched features cannot be guaranteed. To solve this problem, a heterogeneous stitching of X-ray images was proposed. This heterogeneous stitching was completed according to the overlap region based on homographic evaluation. To acquire sufficiently matched features within the limited overlap region, integrated feature detection was used to estimate a homography. The homography was then evaluated to confirm its accuracy. When the estimated homography was incorrect, local regions around the matched feature were derived from integrated feature detection and substituted to re-estimate the homography. Successful X-ray image stitching of the C-arm was achieved by estimating the optimal homography for each image. Based on phantom and ex-vivo experiments using the proposed method, we confirmed a panoramic X-ray image construction that was robust compared to the conventional methods. © 2021, Society for Imaging Informatics in Medicine.
Springer Science and Business Media Deutschland GmbH
Related Researcher
  • 이현기 Lee, HyunKi 지능형로봇연구부
  • Research Interests Machine Vision; Intelligent Robot; Design of Optical Systems
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Appears in Collections:
Department of Robotics and Mechatronics Engineering Surgical Robotics & Augmented Reality Lab 1. Journal Articles
Division of Intelligent Robotics Camera Culture Group 1. Journal Articles


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