2D-3D registration for 3D analysis of lower limb alignment in a weight-bearing condition

Title
2D-3D registration for 3D analysis of lower limb alignment in a weight-bearing condition
Authors
이득희김영준심응준이병훈우성경이건우
Keywords
2D-3D registration; 3D analysis; X-ray; CT; simulated annealing
Issue Date
2018-03
Publisher
Applied Mathematics-A Journal of Chinese Universities
Citation
VOL 33, NO 1-70
Abstract
X-ray imaging is the conventional method for diagnosing the orthopedic condition of a patient. Computerized Tomography(CT) scanning is another diagnostic method that provides patient’s 3D anatomical information. However, both methods have limitations when diagnosing the whole leg; X-ray imaging does not provide 3D information, and normal CT scanning cannot be performed with a standing posture. Obtaining 3D data regarding the whole leg in a standing posture is clinically important because it enables 3D analysis in the weight bearing condition. Based on these clinical needs, a hardware-based bi-plane X-ray imaging system has been developed; it uses two orthogonal X-ray images. However, such methods have not been made available in general clinics because of the hight cost. Therefore, we proposed a widely adaptive method for 2D X-ray image and 3D CT scan data. By this method, it is possible to threedimensionally analyze the whole leg in standing posture. The optimal position that generates the most similar image is the captured X-ray image. The algorithm verifies the similarity using the performance of the proposed method by simulation-based experiments. Then, we analyzed the internal-external rotation angle of the femur using real patient data. Approximately 10.55 degrees of internal rotations were found relative to the defined anterior-posterior direction. In this paper, we present a useful registration method using the conventional X-ray image and 3D CT scan data to analyze the whole leg in the weight-bearing condition.
URI
http://pubs.kist.re.kr/handle/201004/68304
ISSN
1005-1031
Appears in Collections:
KIST Publication > Article
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