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Journal of Medical Imaging

Fully automatic initialization of two-dimensional–three-dimensional medical image registration using hybrid classifier
Author(s): Jing Wu; Emam Elhak Abdel-Fatah; Mohamed R. Mahfouz
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Paper Abstract

X-ray video fluoroscopy along with two-dimensional–three-dimensional (2D-3D) registration techniques is widely used to study joints in vivo kinematic behaviors. These techniques, however, are generally very sensitive to the initial alignment of the 3-D model. We present an automatic initialization method for 2D-3D registration of medical images. The contour of the knee bone or implant was first automatically extracted from a 2-D x-ray image. Shape descriptors were calculated by normalized elliptical Fourier descriptors to represent the contour shape. The optimal pose was then determined by a hybrid classifier combining k-nearest neighbors and support vector machine. The feasibility of the method was first validated on computer synthesized images, with 100% successful estimation for the femur and tibia implants, 92% for the femur and 95% for the tibia. The method was further validated on fluoroscopic x-ray images with all the poses of the testing cases successfully estimated. Finally, the method was evaluated as an initialization of a feature-based 2D-3D registration. The initialized and uninitialized registrations had success rates of 100% and 50%, respectively. The proposed method can be easily utilized for 2D-3D image registration on various medical objects and imaging modalities.

Paper Details

Date Published: 2 June 2015
PDF: 10 pages
J. Med. Img. 2(2) 024007 doi: 10.1117/1.JMI.2.2.024007
Published in: Journal of Medical Imaging Volume 2, Issue 2
Show Author Affiliations
Jing Wu, The Univ. of Tennessee Knoxville (United States)
Emam Elhak Abdel-Fatah, The Univ. of Tennessee Knoxville (United States)
Mohamed R. Mahfouz, The Univ. of Tennessee Knoxville (United States)


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