Interactive initialization of 2D/3D rigid registration

Gong, Ren Hui; Güler, Özgür; Kürklüoğlu, Mustafa; Lovejoy, John F.; Yaniv, Ziv

doi:10.1118/1.4830428

Cited by 14 publications

(5 citation statements)

References 34 publications

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“…The success rate of the registration using Generalized Hough Transform is 95.73%. The interactive initialization method in [14] with average interaction time 132.1 ± 66.4s has an error of 7.4 ± 5.0 mm.…”

Section: Discussionmentioning

confidence: 99%

“…In order to address the problem associated with initialization of a 2D/3D registration task, Gong et al [14] suggested an interactive initialization technique where the user performs the alignment by utilizing a gesture-based interface or an augmented reality environment together with a navigation system. The tedious initialization procedure makes the system impractical in a surgical setting.…”

Section: Related Workmentioning

confidence: 99%

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Pose-aware C-arm for automatic re-initialization of interventional 2D/3D image registration

et al. 2017

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Purpose In minimally invasive interventions assisted by C-arm imaging, there is a demand to fuse the intra-interventional 2D C-arm image with pre-interventional 3D patient data to enable surgical guidance. The commonly used intensity-based 2D/3D registration has a limited capture range and is sensitive to initialization. We propose to utilize an opto/X-ray C-arm system which allows to maintain the registration during intervention by automating the re-initialization for the 2D/3D image registration. Consequently, the surgical workflow is not disrupted and the interaction time for manual initialization is eliminated. Methods We utilize two distinct vision-based tracking techniques to estimate the relative poses between different C-arm arrangements: (1) global tracking using fused depth information and (2) RGBD SLAM system for surgical scene tracking. A highly accurate multi-view calibration between RGBD and C-arm imaging devices is achieved using a custom-made multimodal calibration target. Results Several in vitro studies are conducted on pelvic-femur phantom that is encased in gelatin and covered with drapes to simulate a clinically realistic scenario. The mean target registration errors (mTRE) for re-initialization using depth-only and RGB+depth are 13.23mm and 11.81mm, respectively. 2D/3D registration yielded 75% success rate using this automatic re-initialization, compared to a random initialization which yielded only 23% successful registration. Conclusion The pose-aware C-arm contributes to the 2D/3D registration process by globally re-initializing the relationship of C-arm image and pre-interventional CT data. This system performs inside-out tracking, is self-contained, and does not require any external tracking devices.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Pose-aware C-arm for automatic re-initialization of interventional 2D/3D image registration

et al. 2017

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“…This fitting process is guided by a set of landmarks, which are either specified manually or provided by the dataset. A nonlinear optimization then determines alignment (scaling, rotation, translation), body shape (PCA parameters), and pose (inverse kinematics on joint angles) in order to minimize squared distances of user-selected landmarks and automatically determined closest point correspondences in a non-rigid ICP manner (Bouaziz et al, 2014b). Once the model parameters are optimized, a fine-scale out-of-model deformation improves the matching accuracy and results in the final template fit.…”

Section: Data Preparationmentioning

confidence: 99%

Inside Humans: Creating a Simple Layered Anatomical Model from Human Surface Scans

Komaritzan

Wenninger

Botsch

2021

Front. Virtual Real.

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3D morphable models are widely used to describe the variation of human body shapes. However, these models typically focus on the surface of the human body, since the acquisition of the volumetric interior would require prohibitive medical imaging. In this paper we present a novel approach for creating a volumetric body template and for fitting this template to the surface scan of a person in a just a few seconds. The body model is composed of three surface layers for bones, muscles, and skin, which enclose the volumetric muscle and fat tissue in between them. Our approach includes a data-driven method for estimating the amount of muscle mass and fat mass from a surface scan, which provides more accurate fits to the variety of human body shapes compared to previous approaches. We also show how to efficiently embed fine-scale anatomical details, such as high resolution skeleton and muscle models, into the layered fit of a person. Our model can be used for physical simulation, statistical analysis, and anatomical visualization in computer animation and medical applications, which we demonstrate on several examples.

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“…For the closely related field of intraoperatively correcting registration in video see-through AR, É et al (2018) provide a manual input interface on the AR display device (a tablet computer). Multiple approaches exist that aim to introduce intuitive threedimensional manipulation to the interactive registration process: For 2D/3D registration of x-ray images, Gong et al (2013) propose using hand gestures to spatially manipulate the virtual model relative to the screen's coordinate system. In their second approach, a virtual tool is placed next to the virtual model.…”

Section: Related Workmentioning

confidence: 99%

Towards natural 3D interaction for laparoscopic augmented reality registration

Joeres

Heinrich

Schott

et al. 2020

Computer Methods in Biomechanics and Biomedical Engineering: Im

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Augmented reality (AR) is a widely researched route for navigation support in laparoscopic surgery. Accurate registration is a crucial component for such AR systems. We introduce two methods for interactive registration that aim to be minimally invasive to the workflow and to mimic natural manipulation of 3D objects. The methods utilise spatially tracked laparoscopic tools to manipulate the virtual 3D content. We comparatively evaluated the methods against a reference, landmark-based registration method in a user study with 12 participants. We tested the methods for registration accuracy, time, and subjective usability perception. Our methods did not outperform the reference method on these parameters but showed promising results. The results indicate that our methods present no finalised solutions but that one of them is a promising approach for which we identified concrete improvement measures to be implemented in future research.

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Interactive initialization of 2D/3D rigid registration

Cited by 14 publications

References 34 publications

Pose-aware C-arm for automatic re-initialization of interventional 2D/3D image registration

Pose-aware C-arm for automatic re-initialization of interventional 2D/3D image registration

Inside Humans: Creating a Simple Layered Anatomical Model from Human Surface Scans

Towards natural 3D interaction for laparoscopic augmented reality registration

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