Comparison of Rigid Gradient-Based 2D/3D Registration Using Projection and Back-Projection Strategies - Schaffert, Roman; Wang, Jian; Borsdorf, Anja; Hornegger, Joachim; Maier, Andreas (Bildverarbeitung für die Medizin, 2016)
UnivIS-Import:2018-09-06:Pub.2016.tech.IMMD.IMMD5.compar_0

Depth-Aware Template Tracking for Robust Patient Motion Compensation for Interventional 2-D/3-D Image Fusion - Wang, Jian; Borsdorf, Anja; Endres, Jürgen; Hornegger, Joachim (2013 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC), 2013)
In interventional radiology, pre-operative three dimensional (3-D) images (e.g. CT and MRI) can be fused to the real-time 2-D fluoroscopic images, known as 2-D/3-D image fusion or overlay. 2-D/3-D registration is usually performed at the beginning to ensure an accurate overlay. However, the misalignment caused by patient motion has to be corrected during the procedure. In this paper, we propose an adapted template-based tracking approach that fits well into the novel depth-layer-based framework, where 3-D motion can be estimated by depth-aware tracking in 2-D X-ray images. Templates are generated according to the 2-D/3-D matching procedure, where the 2-D features are matched with the depth layer images generated from the 3-D volume. Our template update strategy takes both initial and current frame into account, which effectively enhances the accuracy of the template tracking. Two strategies are applied to enhance robustness against external disturbances: template lock and motion estimation feedback. The experiment results show that our new approach is capable of estimating 3-D motion and much more robust against external disturbances compared to the Kanade-Lucas-Tomasi tracker that is previously used in the depth-layer-based framework. © 2013 IEEE.
UnivIS-Import:2015-04-16:Pub.2013.tech.IMMD.IMMD5.deptha_0
Keywords: 2D/3D image fusion; depth-aware tracking; motion compensation; template tracking

Depth-Layer Based Patient Motion Compensation for the Overlay of 3D Volumes onto X-Ray Sequences - Wang, Jian; Borsdorf, Anja; Hornegger, Joachim (2013)

Dynamic 2-D/3-D Rigid Registration Framework Using Point-To-Plane Correspondence Model - Wang, Jian; Schaffert, Roman; Borsdorf, Anja; Heigl, Benno; Huang, Xiaolin; Hornegger, Joachim; Maier, Andreas (IEEE Transactions on Medical Imaging, 2017)
In image-guided interventional procedures, live 2-D X-ray images can be augmented with preoperative 3-D computed tomography or MRI images to provide planning landmarks and enhanced spatial perception. An accurate alignment between the 3-D and 2-D images is a prerequisite for fusion applications. This paper presents a dynamic rigid 2-D/3-D registration framework, which measures the local 3-D-to-2-D misalignment and efficiently constrains the update of both planar and non-planar 3-D rigid transformations using a novel point-to-plane correspondence model. In the simulation evaluation, the proposed method achieved a mean 3-D accuracy of 0.07 mm for the head phantom and 0.05 mm for the thorax phantom using single-view X-ray images. In the evaluation on dynamic motion compensation, our method significantly increases the accuracy comparing with the baseline method. The proposed method is also evaluated on a publicly-available clinical angiogram data set with 'gold-standard' registrations. The proposed method achieved a mean 3-D accuracy below 0.8 mm and a mean 2-D accuracy below 0.3 mm using single-view X-ray images. It outperformed the state-of-the-art methods in both accuracy and robustness in single-view registration. The proposed method is intuitive, generic, and suitable for both initial and dynamic registration scenarios.
UnivIS-Import:2017-12-18:Pub.2017.tech.IMMD.IMMD5.dynami
Keywords: dynamic registration; point-to-plane correspondence model; Rigid 2-D/3-D registration

Epipolar Consistency in Fluoroscopy for Image-Based Tracking - Aichert, André; Wang, Jian; Schaffert, Roman; Dörfler, Arnd; Hornegger, Joachim; Maier, Andreas (Proceedings of the British Machine Vision Conference 2015, 2015)
UnivIS-Import:2017-12-18:Pub.2015.tech.IMMD.IMMD5.epipol_3

Epipolar Consistency in Transmission Imaging - Aichert, André; Berger, Martin; Wang, Jian; Maass, Nicole; Dörfler, Arnd; Hornegger, Joachim; Maier, Andreas (IEEE Transactions on Medical Imaging, 2015)
UnivIS-Import:2015-10-26:Pub.2015.tech.IMMD.IMMD5.epipol
Keywords: X-rays; motion estimation; geometry; stereo vision; X-ray tomography.

Gradient-Based Differential Approach for 3-D Motion Compensation in Interventional 2-D/3-D Image Fusion - Wang, Jian; Borsdorf, Anja; Heigl, Benno; Köhler, Thomas; Hornegger, Joachim (International Conference on 3D Vision, 2014)
UnivIS-Import:2015-04-16:Pub.2014.tech.IMMD.IMMD5.gradie_6

Multi-View Depth-Aware Rigid 2-D/3-D Registration - Schaffert, Roman; Wang, Jian; Fischer, Peter; Borsdorf, Anja; Maier, Andreas (2017 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC), 2017)
UnivIS-Import:2018-02-22:Pub.2017.tech.IMMD.IMMD5.multiv

On Feature Tracking in X-Ray Images - Klüppel, Moritz; Wang, Jian; Bernecker, David; Fischer, Peter; Hornegger, Joachim (Bildverarbeitung für die Medizin 2014, 2014)
Feature point tracking and detection of X-ray images is challenging due to overlapping anatomical structures of different depths, which lead to low-contrast images. Tracking of motion in X-ray sequences can support many clinical applications like motion compensation or two- or three-dimensional registration algorithms. This paper is the first to evaluate the performance of several feature tracking and detection algorithms on artificial and real X-ray image sequences, which involve rigid motion as well as external disturbances. A stand-alone application has been developed to provide an overall test bench for all algorithms, realized by OpenCV implementations. Experiments show that the Karhunen Loeve Transform-based Tracker is the most consistent and effective tracking algorithm. Considering external disturbances, template matching provides the most sufficient results. Furthermore, the influence of feature point detection methods on tracking results is shown.
UnivIS-Import:2015-04-16:Pub.2014.tech.IMMD.IMMD5.onfeat

Real-Time-Capable GPU-Framework for Depth-Aware Rigid 2D/3D Registration - Utzschneider, Matthias; Wang, Jian; Schaffert, Roman; Borsdorf, Anja; Maier, Andreas (Bildverarbeitung für die Medizin 2017, 2017)
UnivIS-Import:2017-12-18:Pub.2017.tech.IMMD.IMMD5.realti

Sparse Depth Sampling for Interventional 2-D/3-D Overlay: Theoretical Error Analysis and Enhanced Motion Estimation - Wang, Jian; Riess, Christian; Borsdorf, Anja; Heigl, Benno; Hornegger, Joachim (Proceedings of the 15th International Conference on Computer Analysis of Images and Patterns - Part I, 2013)

Sparse Depth Sampling for Interventional 2-D/3-D Overlay: Theoretical Error Analysis and Enhanced Motion Estimation - Wang, Jian; Riess, Christian; Borsdorf, Anja; Heigl, Benno; Hornegger, Joachim (Computer Analysis of Images and Patterns, 2013)