Non-rigid free-form 2D–3D registration using a B-spline-based statistical deformation model
This paper presents a non-rigid free-from 2D–3D registration approach using a B-spline-based statistical deformation model (SDM). In our approach the B-spline-based SDM is first constructed from a set of training data using a non-rigid registration algorithm based on B-spline free-form deformation t...
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| Vydané v: | Pattern recognition Ročník 63; s. 689 - 699 |
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| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier Ltd
01.03.2017
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| ISSN: | 0031-3203, 1873-5142 |
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| Abstract | This paper presents a non-rigid free-from 2D–3D registration approach using a B-spline-based statistical deformation model (SDM). In our approach the B-spline-based SDM is first constructed from a set of training data using a non-rigid registration algorithm based on B-spline free-form deformation to encode a priori information about the underlying anatomy. A novel intensity-based non-rigid 2D–3D registration algorithm is then presented to iteratively fit the 3D B-spline-based SDM to the 2D X-ray images of an unseen subject, which requires a computationally expensive inversion of the instantiated deformation in each iteration. In this paper, we propose to solve this challenge with a fast 3D B-spline pseudo-inversion algorithm that is implemented on graphics processing unit (GPU). Comprehensive experiments on simulated images of patient data sets, on calibrated C-arm and on X-ray images of cadaveric femurs are designed and conducted to evaluate the performance of the proposed approach. The experimental results demonstrate the efficacy of the present approach.
•A non-rigid free-from 2D–3D registration approach using a B-spline-based statistical deformation model.•A fast and accurate 3D B-spline pseudo-inversion algorithm.•Comprehensive validation.•Evaluate not only the volume reconstruction accuracy but also the cortical bone region reconstruction accuracy. |
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| AbstractList | This paper presents a non-rigid free-from 2D–3D registration approach using a B-spline-based statistical deformation model (SDM). In our approach the B-spline-based SDM is first constructed from a set of training data using a non-rigid registration algorithm based on B-spline free-form deformation to encode a priori information about the underlying anatomy. A novel intensity-based non-rigid 2D–3D registration algorithm is then presented to iteratively fit the 3D B-spline-based SDM to the 2D X-ray images of an unseen subject, which requires a computationally expensive inversion of the instantiated deformation in each iteration. In this paper, we propose to solve this challenge with a fast 3D B-spline pseudo-inversion algorithm that is implemented on graphics processing unit (GPU). Comprehensive experiments on simulated images of patient data sets, on calibrated C-arm and on X-ray images of cadaveric femurs are designed and conducted to evaluate the performance of the proposed approach. The experimental results demonstrate the efficacy of the present approach.
•A non-rigid free-from 2D–3D registration approach using a B-spline-based statistical deformation model.•A fast and accurate 3D B-spline pseudo-inversion algorithm.•Comprehensive validation.•Evaluate not only the volume reconstruction accuracy but also the cortical bone region reconstruction accuracy. |
| Author | Zheng, Guoyan Yu, Weimin Tannast, Moritz |
| Author_xml | – sequence: 1 givenname: Weimin surname: Yu fullname: Yu, Weimin organization: Institute for Surgical Technology and Biomechanics, University of Bern, Switzerland – sequence: 2 givenname: Moritz surname: Tannast fullname: Tannast, Moritz organization: Department of Orthopaedic Surgery, Inselspital, University of Bern, Switzerland – sequence: 3 givenname: Guoyan surname: Zheng fullname: Zheng, Guoyan email: guoyan.zheng@ieee.org, guoyan.zheng@gmail.com organization: Institute for Surgical Technology and Biomechanics, University of Bern, Switzerland |
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